50+ Machine Learning (ML) Jobs in Bangalore (Bengaluru) | Machine Learning (ML) Job openings in Bangalore (Bengaluru)

Experience in working with various ML libraries and packages like Scikit learn, Numpy, Pandas, Tensorflow, Matplotlib, Caffe, etc. 2. Deep Learning Frameworks: PyTorch, spaCy, Keras 3. Deep Learning Architectures: LSTM, CNN, Self-Attention and Transformers 4. Experience in working with Image processing, computer vision is must 5. Designing data science applications, Large Language Models(LLM) , Generative Pre-trained Transformers (GPT), generative AI techniques, Natural Language Processing (NLP), machine learning techniques, Python, Jupyter Notebook, common data science packages (tensorflow, scikit-learn,keras etc.,.) , LangChain, Flask, FastAPI, prompt engineering. 6. Programming experience in Python 7. Strong written and verbal communications 8. Excellent interpersonal and collaboration skills.

Good-to-Have 1. Experience working with vectored databases and graph representation of documents. 2. Experience with building or maintaining MLOps pipelines. 3. Experience in Cloud computing infrastructures like AWS Sagemaker or Azure ML for implementing ML solutions is preferred. 4. Exposure to Docker, Kubernetes

SN Role descriptions / Expectations from the Role

1 Design and implement scalable and efficient data architectures to support generative AI workflows.

2 Fine tune and optimize large language models (LLM) for generative AI, conduct performance evaluation and benchmarking for LLMs and machine learning models

3 Apply prompt engineer techniques as required by the use case

4 Collaborate with research and development teams to build large language models for generative AI use cases, plan and breakdown of larger data science tasks to lower-level tasks

5 Lead junior data engineers on tasks such as design data pipelines, dataset creation, and deployment, use data visualization tools, machine learning techniques, natural language processing , feature engineering, deep learning , statistical modelling as required by the use case.

Role Overview:

Zolvit is looking for a highly skilled and self-driven Lead Machine Learning Engineer / Lead Data Scientist to lead the design and development of scalable, production-grade ML systems. This role is ideal for someone who thrives on solving complex problems using data, is deeply passionate about machine learning, and has a strong understanding of both classical techniques and modern AI systems like Large Language Models (LLMs).

You will work closely with engineering, product, and business teams to identify impactful ML use cases, build data pipelines, design training workflows, and ensure the deployment of robust, high-performance models at scale.

Key Responsibilities:

● Design and implement scalable ML systems, from experimentation to deployment.

● Build and maintain end-to-end data pipelines for data ingestion, preprocessing, feature engineering, and monitoring.

● Lead the development and deployment of ML models across a variety of use cases — including classical ML and LLM-based applications like summarization, classification, document understanding, and more.

● Define model training and evaluation pipelines, ensuring reproducibility and performance tracking.

● Apply statistical methods to interpret data, validate assumptions, and inform modeling decisions.

● Collaborate cross-functionally with engineers, data analysts, and product managers to solve high-impact business problems using ML.

● Ensure proper MLOps practices are in place for model versioning, monitoring, retraining, and performance management.

● Keep up-to-date with the latest advancements in AI/ML, and actively evaluate and incorporate LLM capabilities and frameworks into solutions.

● Mentor junior ML engineers and data scientists, and help scale the ML function across the organization.

Required Qualifications:

● 7+ years of hands-on experience in ML/AI, building real-world ML systems at scale.

● Proven experience with classical ML algorithms (e.g., regression, classification,

clustering, ensemble models).

● Deep expertise in modern LLM frameworks (e.g., OpenAI, HuggingFace, LangChain)

and their integration into production workflows.

● Strong experience with Python, and frameworks such as Scikit-learn, TensorFlow,

PyTorch, or equivalent.

● Solid background in statistics and the ability to apply statistical thinking to real-world

problems.

● Experience with data engineering tools and platforms (e.g., Spark, Airflow, SQL,

Pandas, AWS Glue, etc.).

● Familiarity with cloud services (AWS preferred) and containerization tools (Docker,

Kubernetes) is a plus.

● Strong communication and leadership skills, with experience mentoring and guiding

junior team members.

● Self-starter attitude with a bias for action and ability to thrive in fast-paced environments.

● Master’s degree in Machine Learning, Artificial Intelligence, Statistics, or a related

field is preferred.

Preferred Qualifications:

● Experience deploying ML systems in microservices or event-driven architectures.

● Hands-on experience with vector databases, embeddings, and retrieval-augmented

generation (RAG) systems.

● Understanding of Responsible AI principles and practices.

Why Join Us?

● Lead the ML charter in a mission-driven company solving real-world challenges.

● Work on cutting-edge LLM use cases and platformize ML capabilities for scale.

● Collaborate with a passionate and technically strong team in a high-impact environment.

● Competitive compensation, flexible working model, and ample growth opportunities.

Job Title: Data Science Intern

Location: 6th Sector HSR Layout, Bangalore - Work from Office 5.5 Days

Duration: 3 Months | Stipend: Upto ₹12,000 per month 

Post-Internship Offer (PPO): Available based on performance

🧑‍💻 About the Role

We are looking for a passionate and proactive Data Science Assistant Intern who is equally excited about mentoring learners and gaining hands-on experience with real-world data operations.

This is a 50% technical + 50% mentorship role that blends classroom support with practical data work. Ideal for those looking to build a career in EdTech and Applied Data Science.

🚀 What You'll Do

• Technical Responsibilities (50%)Create and manage dashboards using Python or BI tools like Power BI/Tableau
• Write and optimize SQL queries to extract and analyze backend data
• Support in data gathering, cleaning, and basic analysis
• Contribute to building data pipelines to assist internal decision-making and analytics
• 
  

🚀Mentorship & Support (50%)

• Assist instructors during live Data Science sessions
• Solve doubts related to Python, Machine Learning, and Statistics
• Create and review quizzes, assignments, and other content
• Provide one-on-one academic support and mentoring
• Foster a positive and interactive learning environment

✅ Requirements

• Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field
• Strong knowledge of:
• Python (Data Structures, Functions, OOP, Debugging)
• Pandas, NumPy, Matplotlib
• Machine Learning algorithms (scikit-learn)
• SQL and basic data wrangling
• APIs, Web Scraping, and Time-Series basics
• Advanced Excel: Lookup & reference (VLOOKUP, INDEX+MATCH, XLOOKUP, SUMIF), Logical functions (IF, AND, OR), Statistical & Aggregate Functions: (COUNTIFS, STDEV, PERCENTILE), Text cleanup (TRIM, SUBSTITUTE), Time functions (DATEDIF, NETWORKDAYS), Pivot Tables, Power Query, Conditional Formatting, Data Validation, What-If Analysis, and dynamic dashboards using charts & slicers.
• Excellent communication and interpersonal skills
• Prior mentoring, teaching, or tutoring experience is a big plus
• Passion for helping others learn and grow

Job Title: Data Science Intern

Location: 6th Sector HSR Layout, Bangalore - Work from Office 5.5 Days

Duration: 3 Months | Stipend: Upto ₹12,000 per month 

Post-Internship Offer (PPO): Available based on performance

🧑‍💻 About the Role

We are looking for a passionate and proactive Data Science Assistant Intern who is equally excited about mentoring learners and gaining hands-on experience with real-world data operations.

This is a 50% technical + 50% mentorship role that blends classroom support with practical data work. Ideal for those looking to build a career in EdTech and Applied Data Science.

🚀 What You'll Do

• Technical Responsibilities (50%)Create and manage dashboards using Python or BI tools like Power BI/Tableau
• Write and optimize SQL queries to extract and analyze backend data
• Support in data gathering, cleaning, and basic analysis
• Contribute to building data pipelines to assist internal decision-making and analytics
• 
  

🚀Mentorship & Support (50%)

• Assist instructors during live Data Science sessions
• Solve doubts related to Python, Machine Learning, and Statistics
• Create and review quizzes, assignments, and other content
• Provide one-on-one academic support and mentoring
• Foster a positive and interactive learning environment

✅ Requirements

• Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field
• Strong knowledge of:
• Python (Data Structures, Functions, OOP, Debugging)
• Pandas, NumPy, Matplotlib
• Machine Learning algorithms (scikit-learn)
• SQL and basic data wrangling
• APIs, Web Scraping, and Time-Series basics
• Advanced Excel: Lookup & reference (VLOOKUP, INDEX+MATCH, XLOOKUP), Logical functions (IF, AND, OR), Statistical & Aggregate Functions: (COUNTIFS, STDEV, PERCENTILE), Text cleanup (TRIM, SUBSTITUTE), Time functions (DATEDIF, NETWORKDAYS), Pivot Tables, Power Query, Conditional Formatting, Data Validation, What-If Analysis, and dynamic dashboards using charts & slicers.
• Excellent communication and interpersonal skills
• Prior mentoring, teaching, or tutoring experience is a big plus
• Passion for helping others learn and grow

3+ years of experience in cybersecurity, with a focus on application and cloud security.

· Proficiency in security tools such as Burp Suite, Metasploit, Nessus, OWASP ZAP, and SonarQube.

· Familiarity with data privacy regulations (GDPR, CCPA) and best practices.

· Basic knowledge of AI/ML security frameworks and tools.

Desired Competencies (Technical/Behavioral Competency)

Must-Have 1. Experience in working with various ML libraries and packages like Scikit learn, Numpy, Pandas, Tensorflow, Matplotlib, Caffe, etc.

2. Deep Learning Frameworks: PyTorch, spaCy, Keras

3. Deep Learning Architectures: LSTM, CNN, Self-Attention and Transformers

4. Experience in working with Image processing, computer vision is must

5. Designing data science applications, Large Language Models(LLM) , Generative Pre-trained Transformers (GPT), generative AI techniques, Natural Language Processing (NLP), machine learning techniques, Python, Jupyter Notebook, common data science packages (tensorflow, scikit-learn,kerasetc.,.) , LangChain, Flask,FastAPI, prompt engineering.

6. Programming experience in Python

7. Strong written and verbal communications

8. Excellent interpersonal and collaboration skills.

Good-to-Have 1. Experience working with vectored databases and graph representation of documents.

2. Experience with building or maintaining MLOpspipelines.

3. Experience in Cloud computing infrastructures like AWS Sagemaker or Azure ML for implementing ML solutions is preferred.

4. Exposure to Docker, Kubernetes

Hands-on knowledge in machine learning, deep learning, TensorFlow, Python, NLP 2. Stay up to date on the latest AI emergences relevant to the business domain. 3. Conduct research and development processes for AI strategies. 4. Experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs. 5. Experience with transformer models such as BERT, GPT, RoBERTa, etc, and a solid understanding of their underlying principles is a plus

Good-to-Have 1. Have knowledge of software development methodologies, such as Agile or Scrum 2. Have strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience. 3. Have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face 4. Ensure the quality of code and applications through testing, peer review, and code analysis. 5. Root cause analysis and bugs correction 6. Familiarity with version control systems, preferably Git. 7. Experience with building or maintaining cloud-native applications. 8. Familiarity with cloud platforms such as AWS, Azure, or Google Cloud is Plus

SN Role descriptions / Expectations from the Role

1 Design, Develop and configure GenAI applications to meet the business requirements.

2 Optimizing existing generative AI models for improved performance, scalability, and efficiency

3 Developing and maintaining AI pipelines, including data preprocessing, feature extraction, model training, and evaluation

Technical Skills – Must have  

 Lead the design and development of AI-driven test automation frameworks and solutions.

 Collaborate with stakeholders (e.g., product managers, developers, data scientists) to understand testing requirements and identify areas where AI automation can be effectively implemented.

 Develop and implement test automation strategies for AI-based systems, encompassing various aspects like data generation, model testing, and performance evaluation.

 Evaluate and select appropriate tools and technologies for AI test automation, including AI frameworks, testing tools, and automation platforms.

 Define and implement best practices for AI test automation, covering areas like code standards, test case design, test data management, and ethical considerations.

 Lead and mentor a team of test automation engineers in designing, developing, and executing AI test automation solutions.

 Collaborate with development teams to ensure the testability of AI models and systems, providing guidance and feedback throughout the development lifecycle.

 Analyze test results and identify areas for improvement in the AI automation process, continuously optimizing testing effectiveness and efficiency.

 Stay up-to-date with the latest advancements and trends in AI and automation technologies, actively adapting and implementing new knowledge to enhance testing capabilities.

 Knowledge in Generative AI and Conversational AI for implementation in test automation strategies is highly desirable.

 Proficiency in programming languages commonly used in AI, such as Python, Java, or R.

 Knowledge on AI frameworks and libraries, such as TensorFlow, PyTorch, or scikit-learn.

 Familiarity with testing methodologies and practices, including Agile and DevOps.

 Working experience on Python/Java and Selenium also knowledge in prompt engineering.

Senior Data Engineer Job Description

Overview

The Senior Data Engineer will design, develop, and maintain scalable data pipelines and

infrastructure to support data-driven decision-making and advanced analytics. This role requires deep

expertise in data engineering, strong problem-solving skills, and the ability to collaborate with

cross-functional teams to deliver robust data solutions.

Key Responsibilities

Data Pipeline Development: Design, build, and optimize scalable, secure, and reliable data

pipelines to ingest, process, and transform large volumes of structured and unstructured data.

Data Architecture: Architect and maintain data storage solutions, including data lakes, data

warehouses, and databases, ensuring performance, scalability, and cost-efficiency.

Data Integration: Integrate data from diverse sources, including APIs, third-party systems,

and streaming platforms, ensuring data quality and consistency.

Performance Optimization: Monitor and optimize data systems for performance, scalability,

and cost, implementing best practices for partitioning, indexing, and caching.

Collaboration: Work closely with data scientists, analysts, and software engineers to

understand data needs and deliver solutions that enable advanced analytics, machine

learning, and reporting.

Data Governance: Implement data governance policies, ensuring compliance with data

security, privacy regulations (e.g., GDPR, CCPA), and internal standards.

Automation: Develop automated processes for data ingestion, transformation, and validation

to improve efficiency and reduce manual intervention.

Mentorship: Guide and mentor junior data engineers, fostering a culture of technical

excellence and continuous learning.

Troubleshooting: Diagnose and resolve complex data-related issues, ensuring high

availability and reliability of data systems.

Required Qualifications

Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science,

or a related field.

Experience: 5+ years of experience in data engineering or a related role, with a proven track

record of building scalable data pipelines and infrastructure.

Technical Skills:

Proficiency in programming languages such as Python, Java, or Scala.

Expertise in SQL and experience with NoSQL databases (e.g., MongoDB, Cassandra).

Strong experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services

(e.g., Redshift, BigQuery, Snowflake).

Hands-on experience with ETL/ELT tools (e.g., Apache Airflow, Talend, Informatica) and

data integration frameworks.

Familiarity with big data technologies (e.g., Hadoop, Spark, Kafka) and distributed

systems.

Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes) is a

plus.

Soft Skills:

Excellent problem-solving and analytical skills.

Strong communication and collaboration abilities.

Ability to work in a fast-paced, dynamic environment and manage multiple priorities.

Certifications (optional but preferred): Cloud certifications (e.g., AWS Certified Data Analytics,

Google Professional Data Engineer) or relevant data engineering certifications.

Preferred Qualifica

Experience with real-time data processing and streaming architectures.

Familiarity with machine learning pipelines and MLOps practices.

Knowledge of data visualization tools (e.g., Tableau, Power BI) and their integration with data

pipelines.

Experience in industries with high data complexity, such as finance, healthcare, or

e-commerce.

Work Environment

Location: Hybrid/Remote/On-site (depending on company policy).

Team: Collaborative, cross-functional team environment with data scientists, analysts, and

business stakeholders.

Hours: Full-time, with occasional on-call responsibilities for critical data systems.

About Moative

Moative, an Applied AI Services company, designs AI roadmaps, builds co-pilots and predictive AI solutions for companies in energy, utilities, packaging, commerce, and other primary industries. Through Moative Labs, we aspire to build micro-products and launch AI startups in vertical markets.

Our Past: We have built and sold two companies, one of which was an AI company. Our founders and leaders are Math PhDs, Ivy League University Alumni, Ex-Googlers, and successful entrepreneurs.

Role

We seek experienced ML/AI professionals with strong backgrounds in computer science, software engineering, or related elds to join our Azure-focused MLOps team. If you’re passionate about deploying complex machine learning models in real-world settings, bridging the gap between research and production, and working on high-impact projects, this role is for you.

Work you’ll do

As an operations engineer, you’ll oversee the entire ML lifecycle on Azure—spanning initial proofs-of-concept to large-scale production deployments. You’ll build and maintain automated training, validation, and deployment pipelines using Azure DevOps, Azure ML, and related services, ensuring models are continuously monitored, optimized for performance, and cost-eective. By integrating MLOps practices such as MLow and CI/CD, you’ll drive rapid iteration and experimentation. In close collaboration with senior ML engineers, data scientists, and domain experts, you’ll deliver robust, production-grade ML solutions that directly impact business outcomes. 

Responsibilities

• ML-focused DevOps: Set up robust CI/CD pipelines with a strong emphasis on model versioning, automated testing, and advanced deployment strategies on Azure.
• Monitoring & Maintenance: Track and optimize the performance of deployed models through live metrics, alerts, and iterative improvements.
• Automation: Eliminate repetitive tasks around data preparation, model retraining, and inference by leveraging scripting and infrastructure as code (e.g., Terraform, ARM templates).
• Security & Reliability: Implement best practices for securing ML workows on Azure, including identity/access management, container security, and data encryption.
• Collaboration: Work closely with the data science teams to ensure model performance is within agreed SLAs, both for training and inference.

Skills & Requirements

• 2+ years of hands-on programming experience with Python (PySpark or Scala optional).
• Solid knowledge of Azure cloud services (Azure ML, Azure DevOps, ACI/AKS).
• Practical experience with DevOps concepts: CI/CD, containerization (Docker, Kubernetes), infrastructure as code (Terraform, ARM templates).
• Fundamental understanding of MLOps: MLow or similar frameworks for tracking and versioning.
• Familiarity with machine learning frameworks (TensorFlow, PyTorch, XGBoost) and how to operationalize them in production.
• Broad understanding of data structures and data engineering.

Working at Moative

Moative is a young company, but we believe strongly in thinking long-term, while acting with urgency. Our ethos is rooted in innovation, eiciency and high-quality outcomes. We believe the future of work is AI-augmented and boundary less.

Here are some of our guiding principles:

• Think in decades. Act in hours. As an independent company, our moat is time. While our decisions are for the long-term horizon, our execution will be fast – measured in hours and days, not weeks and months.
• Own the canvas. Throw yourself in to build, x or improve – anything that isn’t done right, irrespective of who did it. Be selsh about improving across the organization – because once the rot sets in, we waste years in surgery and recovery.
• Use data or don’t use data. Use data where you ought to but not as a ‘cover-my-back’ political tool. Be capable of making decisions with partial or limited data. Get better at intuition and pattern-matching. Whichever way you go, be mostly right about it.
• Avoid work about work. Process creeps on purpose, unless we constantly question it. We are deliberate about committing to rituals that take time away from the actual work. We truly believe that a meeting that could be an email, should be an email and you don’t need a person with the highest title to say that loud.
• High revenue per person. We work backwards from this metric. Our default is to automate instead of hiring. We multi-skill our people to own more outcomes than hiring someone who has less to do. We don’t like squatting and hoarding that comes in the form of hiring for growth. High revenue per person comes from high quality work from everyone. We demand it.

If this role and our work is of interest to you, please apply here. We encourage you to apply even if you believe you do not meet all the requirements listed above.

That said, you should demonstrate that you are in the 90th percentile or above. This may mean that you have studied in top-notch institutions, won competitions that are intellectually demanding, built something of your own, or rated as an outstanding performer by your current or previous employers.

The position is based out of Chennai. Our work currently involves significant in-person collaboration and we expect you to work out of our offices in Chennai.

·        Develop and maintain scalable back-end applications using Python frameworks such as Flask/Django/FastAPI.

·        Design, build, and optimize data pipelines for ETL processes using tools like PySpark, Airflow, and other similar technologies.

·        Work with relational and NoSQL databases to manage and process large datasets efficiently.

Collaborate with data scientists to clean, transform, and prepare data for analytics and machine learning models.

Work in a dynamic environment, at the intersection of software development and data engineering.

Key Responsibilities

• Develop and maintain backend services and APIs using Java (Spring Boot preferred).
• Integrate Large Language Models (LLMs) and Generative AI models (e.g., OpenAI, Hugging Face, LangChain) into applications.
• Collaborate with data scientists to build data pipelines and enable intelligent application features.
• Design scalable systems to support AI model inference and deployment.
• Work with cloud platforms (AWS, GCP, or Azure) for deploying AI-driven services.
• Write clean, maintainable, and well-tested code.
• Participate in code reviews and technical discussions.

Required Skills

• 3–5 years of experience in Java development (preferably with Spring Boot).
• Experience working with RESTful APIs, microservices, and cloud-based deployments.
• Exposure to LLMs, NLP, or GenAI tools (OpenAI, Cohere, Hugging Face, LangChain, etc.).
• Familiarity with Python for data science/ML integration is a plus.
• Good understanding of software engineering best practices (CI/CD, testing, etc.).
• Ability to work collaboratively in cross-functional teams.

Desired Competencies (Technical/Behavioral Competency)

Must-Have

1. Experience in working with various ML libraries and packages like Scikit learn, Numpy, Pandas, Tensorflow, Matplotlib, Caffe, etc.
2. Deep Learning Frameworks: PyTorch, spaCy, Keras
3. Deep Learning Architectures: LSTM, CNN, Self-Attention and Transformers
4. Experience in working with Image processing, computer vision is must
5. Designing data science applications, Large Language Models(LLM) , Generative Pre-trained Transformers (GPT), generative AI techniques, Natural Language Processing (NLP), machine learning techniques, Python, Jupyter Notebook, common data science packages (tensorflow, scikit-learn,kerasetc.,.) , LangChain, Flask,FastAPI, prompt engineering.
6. Programming experience in Python
7. Strong written and verbal communications
8. Excellent interpersonal and collaboration skills.

Role descriptions / Expectations from the Role

Design and implement scalable and efficient data architectures to support generative AI workflows.

Fine tune and optimize large language models (LLM) for generative AI, conduct performance evaluation and benchmarking for LLMs and machine learning models

Apply prompt engineer techniques as required by the use case

Collaborate with research and development teams to build large language models for generative AI use cases, plan and breakdown of larger data science tasks to lower-level tasks

Lead junior data engineers on tasks such as design data pipelines, dataset creation, and deployment, use data visualization tools, machine learning techniques, natural language processing , feature engineering, deep learning , statistical modelling as required by the use case.

Desired Competencies (Technical/Behavioral Competency)

Must-Have

1. Hands-on knowledge in machine learning, deep learning, TensorFlow, Python, NLP
2. Stay up to date on the latest AI emergences relevant to the business domain.
3. Conduct research and development processes for AI strategies.

4.     Experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.

5.     Experience with transformer models such as BERT, GPT, RoBERTa, etc, and a solid understanding of their underlying principles is a plus

Good-to-Have

1. Have knowledge of software development methodologies, such as Agile or Scrum
2. Have strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.
3. Have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face
4. Ensure the quality of code and applications through testing, peer review, and code analysis.
5. Root cause analysis and bugs correction
6. Familiarity with version control systems, preferably Git.
7. Experience with building or maintaining cloud-native applications.
8. Familiarity with cloud platforms such as AWS, Azure, or Google Cloud is Plus

Design and implement scalable and efficient data architectures to support generative AI workflows.

2 Fine tune and optimize large language models (LLM) for generative AI, conduct performance evaluation and benchmarking for LLMs and machine learning models

3 Apply prompt engineer techniques as required by the use case

4 Collaborate with research and development teams to build large language models for generative AI use cases, plan and breakdown of larger data science tasks to lower-level tasks

5 Lead junior data engineers on tasks such as design data pipelines, dataset creation, and deployment, use data visualization tools, machine learning techniques, natural language processing , feature engineering, deep learning , statistical modelling as required by the use case.

• Design, develop, and maintain data pipelines and ETL workflows on AWS platform
• Work with AWS services like S3, Glue, Lambda, Redshift, EMR, and Athena for data ingestion, transformation, and analytics
• Collaborate with Data Scientists, Analysts, and Business teams to understand data requirements
• Optimize data workflows for performance, scalability, and reliability
• Troubleshoot data issues, monitor jobs, and ensure data quality and integrity
• Write efficient SQL queries and automate data processing tasks
• Implement data security and compliance best practices
• Maintain technical documentation and data pipeline monitoring dashboards

We are looking for a Senior AI/ML Engineer with expertise in Generative AI (GenAI) integrations, APIs, and Machine Learning (ML) algorithms who should have strong hands-on experience in Python and statistical and predictive modeling.

Key Responsibilities:

• Develop and integrate GenAI solutions using APIs and custom models.

• Design, implement, and optimize ML algorithms for predictive modeling and data-driven insights.

• Leverage statistical techniques to improve model accuracy and performance.

• Write clean, well-documented, and testable code while adhering to

coding standards and best practices.

Required Skills:

• 4+ years of experience in AI/ML, with a strong focus on GenAI integrations and APIs.

• Proficiency in Python, including libraries like TensorFlow, PyTorch, Scikit-learn, and Pandas.

• Strong expertise in statistical modeling and ML algorithms (Regression, Classification, Clustering, NLP, etc.).

• Hands-on experience with RESTful APIs and AI model deployment.

What You will do:

● Create beautiful software experiences for our clients using design thinking, lean, and agile methodology.

● Work on software products designed from scratch using the latest cutting-edge technologies, platforms, and languages such as NodeJS, JavaScript.

● Work in a dynamic, collaborative, transparent, non-hierarchical culture.

● Work in collaborative, fast-paced,d and value-driven teams to build innovative customer experiences for our clients.

● Help to grow the next generation of developers and have a positive impact on the industry.

Basic Qualifications :

● Experience: 4+ years.

● Hands-on development experience with a broad mix of languages such as NodeJS,

● Server-side development experience, mainly in NodeJS, can be considerable

● UI development experience in AngularJS

● Passion for software engineering and following the best coding concepts .

● Good to great problem-solving and communication skills.

Nice to have Qualifications:

● Product and customer-centric mindset.

● Great OO skills, including design patterns.

● Experience with devops, continuous integration & deployment.

● Exposure to big data technologies, Machine Learning, and NLP will be a plus.

What You will do:

● Play the role of Data Analyst / ML Engineer

● Collection, cleanup, exploration and visualization of data

● Perform statistical analysis on data and build ML models

● Implement ML models using some of the popular ML algorithms

● Use Excel to perform analytics on large amounts of data

● Understand, model and build to bring actionable business intelligence out of data that is available in different formats

● Work with data engineers to design, build, test and monitor data pipelines for ongoing business operations







Basic Qualifications:

● Experience: 4+ years.

● Hands-on development experience playing the role of Data Analyst and/or ML Engineer.

● Experience in working with excel for data analytics

● Experience with statistical modelling of large data sets

● Experience with ML models and ML algorithms

● Coding experience in Python







Nice to have Qualifications:

● Experience with wide variety of tools used in ML

● Experience with Deep learning







Benefits:

● Competitive salary.

● Hybrid work model.

● Learning and gaining experience rapidly.

● Reimbursement for basic working set up at home.

● Insurance (including a top up insurance for COVID

Responsibilities

• Model Development and Optimization: Design, build, and deploy NLP models, including transformer models (e.g., BERT, GPT, T5) and other SOTA architectures, as well as traditional machine learning algorithms (e.g., SVMs, Logistic Regression) for specific applications.

• Data Processing and Feature Engineering: Develop robust pipelines for text preprocessing, feature extraction, and data augmentation for structured and unstructured data.

• Model Fine-Tuning and Transfer Learning:

Fine-tune large language models for specific applications, leveraging transfer learning techniques, domain adaptation, and a mix of deep learning and traditional ML models.

• Performance Optimization: Optimize model performance for scalability and latency, applying techniques such as quantization, ONNX formats etc.

• Research and Innovation: Stay updated with the latest research in NLP, Deep Learning, and Generative AI, applying innovative solutions and techniques (e.g., RAG applications, Prompt engineering, Self-supervised learning).

• Stakeholder Communication: Collaborate with stakeholders to gather requirements, conduct due diligence, and communicate project updates effectively, ensuring alignment between technical solutions and business goals.

• Evaluation and Testing: Establish metrics, benchmarks, and methodologies for model evaluation, including cross-validation, and error analysis, ensuring models meet accuracy, fairness, and reliability standards. • Deployment and Monitoring: Oversee the deployment of NLP models in production, ensuring seamless integration, model monitoring, and retraining processes. 

JioTesseract, a digital arm of Reliance Industries, is India's leading and largest AR/VR organization with the mission to democratize mixed reality for India and the world. We make products at the cross of hardware, software, content and services with focus on making India the leader in spatial computing. We specialize in creating solutions in AR, VR and AI, with some of our notable products such as JioGlass, JioDive, 360 Streaming, Metaverse, AR/VR headsets for consumers and enterprise space.

Mon-fri role, In office, with excellent perks and benefits!

Position Overview

We are seeking a Software Architect to lead the design and development of high-performance robotics and AI software stacks utilizing NVIDIA technologies. This role will focus on defining scalable, modular, and efficient architectures for robot perception, planning, simulation, and embedded AI applications. You will collaborate with cross-functional teams to build next-generation autonomous systems 9

Key Responsibilities:

1. System Architecture & Design

● Define scalable software architectures for robotics perception, navigation, and AI-driven decision-making.

● Design modular and reusable frameworks that leverage NVIDIA’s Jetson, Isaac ROS, Omniverse, and CUDA ecosystems.

● Establish best practices for real-time computing, GPU acceleration, and edge AI inference.

2. Perception & AI Integration

● Architect sensor fusion pipelines using LIDAR, cameras, IMUs, and radar with DeepStream, TensorRT, and ROS2.

● Optimize computer vision, SLAM, and deep learning models for edge deployment on Jetson Orin and Xavier.

● Ensure efficient GPU-accelerated AI inference for real-time robotics applications.

3. Embedded & Real-Time Systems

● Design high-performance embedded software stacks for real-time robotic control and autonomy.

● Utilize NVIDIA CUDA, cuDNN, and TensorRT to accelerate AI model execution on Jetson platforms.

● Develop robust middleware frameworks to support real-time robotics applications in ROS2 and Isaac SDK.

4. Robotics Simulation & Digital Twins

● Define architectures for robotic simulation environments using NVIDIA Isaac Sim & Omniverse.

● Leverage synthetic data generation (Omniverse Replicator) for training AI models.

● Optimize sim-to-real transfer learning for AI-driven robotic behaviors.

5. Navigation & Motion Planning

● Architect GPU-accelerated motion planning and SLAM pipelines for autonomous robots.

● Optimize path planning, localization, and multi-agent coordination using Isaac ROS Navigation.

● Implement reinforcement learning-based policies using Isaac Gym.

6. Performance Optimization & Scalability

● Ensure low-latency AI inference and real-time execution of robotics applications.

● Optimize CUDA kernels and parallel processing pipelines for NVIDIA hardware.

● Develop benchmarking and profiling tools to measure software performance on edge AI devices.

Required Qualifications:

● Master’s or Ph.D. in Computer Science, Robotics, AI, or Embedded Systems.

● Extensive experience (7+ years) in software development, with at least 3-5 years focused on architecture and system design, especially for robotics or embedded systems.

● Expertise in CUDA, TensorRT, DeepStream, PyTorch, TensorFlow, and ROS2.

● Experience in NVIDIA Jetson platforms, Isaac SDK, and GPU-accelerated AI.

● Proficiency in programming languages such as C++, Python, or similar, with deep understanding of low-level and high-level design principles.

● Strong background in robotic perception, planning, and real-time control.

● Experience with cloud-edge AI deployment and scalable architectures.

Preferred Qualifications

● Hands-on experience with NVIDIA DRIVE, NVIDIA Omniverse, and Isaac Gym

● Knowledge of robot kinematics, control systems, and reinforcement learning

● Expertise in distributed computing, containerization (Docker), and cloud robotics

● Familiarity with automotive, industrial automation, or warehouse robotics

● Experience designing architectures for autonomous systems or multi-robot systems.

● Familiarity with cloud-based solutions, edge computing, or distributed computing for robotics

● Experience with microservices or service-oriented architecture (SOA)

● Knowledge of machine learning and AI integration within robotic systems

● Knowledge of testing on edge devices with HIL and simulations (Isaac Sim, Gazebo, V-REP etc.)

Link to apply- https://tally.so/r/w8RpLk

About Us

At GreenStitch, we are on a mission to revolutionise the fashion and textile industry through cutting-edge climate-tech solutions. We are looking for a highly skilled Data Scientist-I with expertise in NLP and Deep Learning to drive innovation in our data-driven applications. This role requires a strong foundation in AI/ML, deep learning, and software engineering to develop impactful solutions aligned with our sustainability and business objectives.

The ideal candidate demonstrates up-to-date expertise in Deep Learning and NLP and applies it to the development, execution, and improvement of applications. This role involves supporting and aligning efforts to meet both customer and business needs.

You will play a key role in building strong relationships with stakeholders, identifying business challenges, and implementing AI-driven solutions. You should be adaptable to competing demands, organisational changes, and new responsibilities while upholding GreenStitch’s mission, values, and ethical standards.

What You’ll Do:

• AI-Powered Applications: Build and deploy AI-driven applications leveraging Generative AI and NLP to enhance user experience and operational efficiency.
• Model Development: Design and implement deep learning models and machine learning pipelines to solve complex business challenges.
• Cross-Functional Collaboration: Work closely with product managers, engineers, and business teams to identify AI/ML opportunities.
• Innovation & Experimentation: Stay up-to-date with the latest AI/ML advancements, rapidly prototype solutions, and iterate on ideas for continuous improvement.
• Scalability & Optimisation: Optimise AI models for performance, scalability, and real-world impact, ensuring production readiness.
• Knowledge Sharing & Thought Leadership: Contribute to publications, patents, and technical forums; represent GreenStitch in industry and academic discussions.
• Compliance & Ethics: Model compliance with company policies and ensure AI solutions align with ethical standards and sustainability goals.
• Communication: Translate complex AI/ML concepts into clear, actionable insights for business stakeholders.

What You’ll Bring:

• Education: Bachelors/Master’s degree in Data Science, Computer Science, AI, or a related field.
• Experience: 1-3 years of hands-on experience in AI/ML, NLP, and Deep Learning.
• Technical Expertise: Strong knowledge of transformer-based models (GPT, BERT, etc.), deep learning frameworks (TensorFlow, PyTorch), and cloud platforms (Azure, AWS, GCP).
• Software Development: Experience in Python, Java, or similar languages, and familiarity with MLOps tools.
• Problem-Solving: Ability to apply AI/ML techniques to real-world challenges with a data-driven approach.
• Growth Mindset: Passion for continuous learning and innovation in AI and climate-tech applications.
• Collaboration & Communication: Strong ability to work with cross-functional teams, communicate complex ideas, and drive AI adoption.

Why GreenStitch?

GreenStitch is at the forefront of climate-tech innovation, helping businesses in the fashion and textile industry reduce their environmental footprint. By joining us, you will:

• Work on high-impact AI projects that contribute to sustainability and decarbonisation.
• Be part of a dynamic and collaborative team committed to making a difference.
• Enjoy a flexible, hybrid work model that supports professional growth and work-life balance.
• Receive competitive compensation and benefits, including healthcare, parental leave, and learning opportunities.

Location: Bangalore(India)

Employment Type: Full Time, Permanent

Industry Type: Climate-Tech / Fashion-Tech

Department: Data Science & Machine Learning

Join us in shaping the future of sustainable fashion with cutting-edge AI solutions! 🚀

Level of skills and experience:

5 years of hands-on experience in using Python, Spark,Sql.

Experienced in AWS Cloud usage and management.

Experience with Databricks (Lakehouse, ML, Unity Catalog, MLflow).

Experience using various ML models and frameworks such as XGBoost, Lightgbm, Torch.

Experience with orchestrators such as Airflow and Kubeflow.

Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes).

Fundamental understanding of Parquet, Delta Lake and other data file formats.

Proficiency on an IaC tool such as Terraform, CDK or CloudFormation.

Strong written and verbal English communication skill and proficient in communication with non-technical stakeholderst

We are seeking a Senior Data Scientist with hands-on experience in Generative AI (GenAI) and Large Language Models (LLM). The ideal candidate will have expertise in building, fine-tuning, and deploying LLMs, as well as managing the lifecycle of AI models through LLMOps practices. You will play a key role in driving AI innovation, developing advanced algorithms, and optimizing model performance for various business applications.

Key Responsibilities:

• Develop, fine-tune, and deploy Large Language Models (LLM) for various business use cases.
• Implement and manage the operationalization of LLMs using LLMOps best practices.
• Collaborate with cross-functional teams to integrate AI models into production environments.
• Optimize and troubleshoot model performance to ensure high accuracy and scalability.
• Stay updated with the latest advancements in Generative AI and LLM technologies.

Required Skills and Qualifications:

• Strong hands-on experience with Generative AI, LLMs, and NLP techniques.
• Proven expertise in LLMOps, including model deployment, monitoring, and maintenance.
• Proficiency in programming languages like Python and frameworks such as TensorFlow, PyTorch, or Hugging Face.
• Solid understanding of AI/ML algorithms and model optimization.

Overview

C5i is a pure-play AI & Analytics provider that combines the power of human perspective with AI technology to deliver trustworthy intelligence. The company drives value through a comprehensive solution set, integrating multifunctional teams that have technical and business domain expertise with a robust suite of products, solutions, and accelerators tailored for various horizontal and industry-specific use cases. At the core, C5i’s focus is to deliver business impact at speed and scale by driving adoption of AI-assisted decision-making.

C5i caters to some of the world’s largest enterprises, including many Fortune 500 companies. The company’s clients span Technology, Media, and Telecom (TMT), Pharma & Lifesciences, CPG, Retail, Banking, and other sectors. C5i has been recognized by leading industry analysts like Gartner and Forrester for its Analytics and AI capabilities and proprietary AI-based platforms.

Global offices

United States | Canada | United Kingdom | United Arab of Emirates | India

Job Responsibilities

• Solve complex business problems by applying NLP, CV and Machine Learning techniques. Integrate these algorithms into multiple product and solution offerings.
• Conduct research to advance the field of generative AI, including staying up-to-date with the latest developments and techniques. Develop new generative models or improve existing ones.
• Build cognitive capabilities in multiple product and solution offerings.
• Systemic study of latest research and industry developments in Artificial Intelligence. Leverage these developments to solve real-world business problems.
• Envisage next-generation challenges and recommend solutions to solve them.
• Facilitate the IP generation process in the organization and works towards patenting of inventions.

Requirements & Qualifications:

• B.E/B.TECH/MS/M.TECH/MCA.
• Knowledge / Competency / Skills: - Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP).
• Knowledge of various Generative AI models and Prompt Engineering.
• Hands-on coding skills in Python, at least 4 years’ python experience. (Preferred) Strong NLP skills.

C5i is proud to be an equal opportunity employer. We are committed to equal employment opportunity regardless of race, color, religion, sex, sexual orientation, age, marital status, disability, gender identity, etc. If you have a disability or special need that requires accommodation, please keep us informed about the same at the hiring stages for us to factor necessary accommodations.

Key Responsibilities:

• Develop and maintain scalable Python applications for AI/ML projects.
• Design, train, and evaluate machine learning models for classification, regression, NLP, computer vision, or recommendation systems.
• Collaborate with data scientists, ML engineers, and software developers to integrate models into production systems.
• Optimize model performance and ensure low-latency inference in real-time environments.
• Work with large datasets to perform data cleaning, feature engineering, and data transformation.
• Stay current with new developments in machine learning frameworks and Python libraries.
• Write clean, testable, and efficient code following best practices.
• Develop RESTful APIs and deploy ML models via cloud or container-based solutions (e.g., AWS, Docker, Kubernetes).

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Thirega@ vysystems dot com - WhatsApp - 91Five0033Five2Three

As the Lead Robotics Software Engineer and Founding Engineer, you will architect and lead the development of robotic software for AI Robots. You’ll design and implement robot manipulation and control algorithm, motion planning systems and navigation system leading the development of robust, scalable solutions that redefine AI-driven robotics in construction.

Key Responsibilities:

• ● Design and optimize motion planning and trajectory systems for robotic construction equipment
• ● Develop control systems for autonomous construction robots
• ● Build and maintain simulation environments for system validation
• ● Implement sensor fusion algorithms for improved robot perception and decision-making
• ● Lead the development of advanced algorithms for robot navigation and control
• ● Collaborate with cross-functional teams to deliver scalable robotics solutions
• Qualifications and Skills:
• ● Bachelor's/Master's (MS or PhD) in Robotics, Computer Science, AI, ML, or related field
• ● 2-7 years of experience in Robotics, Manipulator systems, Control Systems, localization,
• mapping, and navigation
• ● Proficiency in MoveIt2 for manipulation stack, and experience with simulation tools like
• Gazebo, RViz, and NVIDIA Isaac Sim
• ● Strong understanding of control systems, including sensor fusion, Kalman filters, motion
• planning, and trajectory optimization
• ● Excellent programming skills in Python & C++ with familiarity in ROS2
• ● Ability to lead and thrive in a fast-paced startup environment
• Why you should apply:
• ● Join a dynamic startup and work directly with the founders to shape the future of robotics in construction
• ● Be part of a mission to create intelligent robots that eliminate the need for human labour in harsh and unsafe environments
• ● Experience the thrill of building not just a product, but a company from the ground up 

Algorithm Development: Design and implement algorithms, neural networks, and other machine learning techniques to 

simulate human intelligence process 

∙Model Creation: Develop and validate algorithms, neural networks, and other machine learning models. 

∙Generative AI: Specialize in generative AI, which involves creating AI systems that autonomously generate content such as 

text, images, and music. 

∙Machine Learning: Leverage your expertise in machine learning to train models on large datasets and optimize them for 

creative content generation. 

∙Natural Language Processing (NLP): Apply NLP techniques for text generation projects, including text parsing, sentiment 

analysis, and the use of transformer models like GPT. 

∙Data Management: Handle data pre-processing, augmentation, and synthetic data generation. 

Hard Skills: 

∙Advanced Programming: Proficiency in programming languages such as Python, along with AI-centric libraries like 

TensorFlow, PyTorch, and Keras. 

∙Generative Models: Expertise in generative models, including Generative Adversarial Networks (GANs) and Variational 

Autoencoders (VAEs). 

∙NLP: Familiarity with NLP techniques for text generation. 

∙Data Management: Knowledge of data pre-processing, augmentation, and synthetic data generation. 

Hard Skills: 

∙Creativity: Ability to think creatively and solve complex, creative challenges using AI. 

∙Collaboration: Work effectively with researchers, engineers, and other team members. 

∙Continuous Learning: Stay updated with evolving AI technologies and applications. 

Certifications Needed:  

∙Bachelor’s or master’s degree in computer science, Artificial Intelligence, or related fields. 

∙Proven experience in machine learning, generative AI, 

Role Overview:

We are looking for a skilled Data Scientist with expertise in data analytics, machine learning, and AI to join our team. The ideal candidate will have a strong command of data tools, programming, and knowledge of LLMs and Generative AI, contributing to the growth and automation of our business processes.

Key Responsibilities:

1. Data Analysis & Visualization:

• Develop and manage data pipelines, ensuring data accuracy and integrity.
• Design and implement insightful dashboards using Power BI to help stakeholders make data-driven decisions.
• Extract and analyze complex data sets using SQL to generate actionable insights

2 Machine Learning & AI Models:

• Build and deploy machine learning models to optimize key business functions like discount management, lead qualification, and process automation.
• Apply Natural Language Processing (NLP) techniques for text extraction, analysis, and classification from customer documents.
• Implement and fine-tune Generative AI models and large language models (LLMs) for various business applications, including prompt engineering for automation tasks.

3 Automation & Innovation:

• Use AI to streamline document verification, data extraction, and customer interaction processes.
• Innovate and automate manual processes, creating AI-driven solutions for internal teams and customer-facing systems.
• Stay abreast of the latest advancements in machine learning, NLP, and generative AI, applying them to real-world business challenges.

Qualifications:

• Bachelor's or Master’s degree in Computer Science, Data Science, Statistics, or related field.
• 4-7 years of experience as a Data Scientist, with proficiency in Python, SQL, Power BI, and Excel.
• Expertise in building machine learning models and utilizing NLP techniques for text processing and automation.
• Experience in working with large language models (LLMs) and generative AI to create efficient and scalable solutions.
• Strong problem-solving skills, with the ability to work independently and in teams.
• Excellent communication skills, with the ability to present complex data in a simple, actionable way to non-technical stakeholders.

If you’re excited about leveraging data and AI to solve real-world problems, we’d love to have you on our team!

Company: Optimum Solutions

About the company: Optimum solutions is a leader in a sheet metal industry, provides sheet metal solutions to sheet metal fabricators with a proven track record of reliable product delivery. Starting from tools through software, machines, we are one stop shop for all your technology needs.

Role Overview:

• Creating and managing database schemas that represent and support business processes, Hands-on experience in any SQL queries and Database server wrt managing deployment.
• Implementing automated testing platforms, unit tests, and CICD Pipeline
• Proficient understanding of code versioning tools, such as GitHub, Bitbucket, ADO
• Understanding of container platform, such as Docker

Job Description

• We are looking for a good Python Developer with Knowledge of Machine learning and deep learning framework.
• Your primary focus will be working the Product and Usecase delivery team to do various prompting for different Gen-AI use cases
• You will be responsible for prompting and building use case Pipelines
• Perform the Evaluation of all the Gen-AI features and Usecase pipeline

Position: AI ML Engineer

Location: Chennai (Preference) and Bangalore

Minimum Qualification:  Bachelor's degree in computer science, Software Engineering, Data Science, or a related field.

Experience:  4-6 years

CTC: 16.5 - 17 LPA

Employment Type:  Full Time

Key Responsibilities:

• Take care of entire prompt life cycle like prompt design, prompt template creation, prompt tuning/optimization for various Gen-AI base models
• Design and develop prompts suiting project needs
• Lead and manage team of prompt engineers
• Stakeholder management across business and domains as required for the projects
• Evaluating base models and benchmarking performance
• Implement prompt gaurdrails to prevent attacks like prompt injection, jail braking and prompt leaking
•  Develop, deploy and maintain auto prompt solutions
• Design and implement minimum design standards for every use case involving prompt engineering

Skills and Qualifications

• Strong proficiency with Python, DJANGO framework and REGEX
• Good understanding of Machine learning framework Pytorch and Tensorflow
• Knowledge of Generative AI and RAG Pipeline
• Good in microservice design pattern and developing scalable application.
• Ability to build and consume REST API
• Fine tune and perform code optimization for better performance.
• Strong understanding on OOP and design thinking
• Understanding the nature of asynchronous programming and its quirks and workarounds
• Good understanding of server-side templating languages
• Understanding accessibility and security compliance, user authentication and authorization between multiple systems, servers, and environments
• Integration of APIs, multiple data sources and databases into one system
• Good knowledge in API Gateways and proxies, such as WSO2, KONG, nginx, Apache HTTP Server.
• Understanding fundamental design principles behind a scalable and distributed application
• Good working knowledge on Microservices architecture, behaviour, dependencies, scalability etc.
• Experience in deploying on Cloud platform like Azure or AWS
• Familiar and working experience with DevOps tools like Azure DEVOPS, Ansible, Jenkins, Terraform

Job Purpose and Impact:

The Sr. Generative AI Engineer will architect, design and develop new and existing GenAI solutions for the organization. As a Generative AI Engineer, you will be responsible for developing and implementing products using cutting-edge generative AI and RAG to solve complex problems and drive innovation across our organization. You will work closely with data scientists, software engineers, and product managers to design, build, and deploy AI-powered solutions that enhance our products and services in Cargill. You will bring order to ambiguous scenarios and apply in depth and broad knowledge of architectural, engineering and security practices to ensure your solutions are scalable, resilient and robust and will share knowledge on modern practices and technologies to the shared engineering community.

Key Accountabilities:

• Apply software and AI engineering patterns and principles to design, develop, test, integrate, maintain and troubleshoot complex and varied Generative AI software solutions and incorporate security practices in newly developed and maintained applications.

• Collaborate with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.

• Conduct research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques and identify opportunities to integrate them into our products and services, optimizing existing generative AI models and RAG for improved performance, scalability, and efficiency, developing and maintaining pipelines and RAG solutions including data preprocessing, prompt engineering, benchmarking and fine-tuning.

• Develop clear and concise documentation, including technical specifications, user guides and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.

• Participate in the engineering community by maintaining and sharing relevant technical approaches and modern skills in AI.

• Contribute to the establishment of best practices and standards for generative AI development within the organization.

• Independently handle complex issues with minimal supervision, while escalating only the most complex issues to appropriate staff.

Minimum Qualifications:

• Bachelor’s degree in a related field or equivalent experience

• Minimum of five years of related work experience

• You are proficient in Python and have experience with machine learning libraries and frameworks

• Have deep understanding of industry leading Foundation Model capabilities and its application.

• You are familiar with cloud-based Generative AI platforms and services

• Full stack software engineering experience to build products using Foundation Models

• Confirmed experience architecting applications, databases, services or integrations.

Internship Opportunity at REDHILL SOFTEC

Position: Software Intern

Duration: 3 Months

Domains: Machine Learning or Full Stack Web Development

Working Hours: 10 AM - 6 PM

About REDHILL SOFTEC:

REDHILL SOFTEC is a dynamic and innovative tech company committed to fostering talent and driving technological advancements. We are excited to announce an exclusive internship opportunity for MCA students passionate about Machine Learning or Full Stack Web Development.

Internship Details:

Duration: The internship spans 3 months, offering a deep dive into either Machine Learning or Full Stack Web Development.

Domains:

Machine Learning: Work on cutting-edge ML projects, learning and applying various algorithms and data analysis techniques.

Full Stack Web Development: Gain hands-on experience in both front-end and back-end development, working with the latest web technologies.

Stipend: This is an unpaid internship designed to provide valuable industry experience and skill development.

Working Hours: Interns are expected to work from 10 AM to 6 PM, ensuring a full-time immersive experience.

What We Offer:

Hands-on Experience: Engage in real-world projects that enhance your technical skills and industry knowledge.

Mentorship: Learn from experienced professionals who will guide and support you throughout the internship.

Skill Development: Acquire practical skills in Machine Learning or Full Stack Web Development, making you industry-ready.

Networking: Connect with industry experts and like-minded peers, building a strong professional network.

Who Should Apply:

MCA/BE/BCA students with a keen interest in Machine Learning or Full Stack Web Development.

Individuals looking to gain practical industry experience and enhance their technical skills.

Self-motivated learners eager to work on real-world projects and solve challenging problems.

How to Apply:

Interested candidates can apply by visiting our website and completing the registration process. Remember, spots are limited, and early applications are encouraged to secure your place in this enriching program.

Join REDHILL SOFTEC and take a significant step towards a successful career in technology!

REDHILL SOFTEC

Vijayanagar Bangalore

www.redhillsoftec.com

We look forward to welcoming passionate and driven interns to our team!

Sizzle is an exciting new startup that’s changing the world of gaming.  At Sizzle, we’re building AI to automate gaming highlights, directly from Twitch and YouTube streams. We’re looking for a superstar Python expert to help develop and deploy our AI pipeline. The main task will be deploying models and algorithms developed by our AI team, and keeping the daily production pipeline running. Our pipeline is centered around several microservices, all written in Python, that coordinate their actions through a database. We’re looking for developers with deep experience in Python including profiling and improving the performance of production code, multiprocessing / multithreading, and managing a pipeline that is constantly running. AI/ML experience is a plus, but not necessary. AWS / docker / CI/CD practices are also a plus. If you are a gamer or streamer, or enjoy watching video games and streams, that is also definitely a plus :-)

You will be responsible for:

• Building Python scripts to deploy our AI components into pipeline and production
• Developing logic to ensure multiple different AI components work together seamlessly through a microservices architecture
• Managing our daily pipeline on both on-premise servers and AWS
• Working closely with the AI engineering, backend and frontend teams

You should have the following qualities:

• Deep expertise in Python including:
• Multiprocessing / multithreaded applications
• Class-based inheritance and modules
• DB integration including pymongo and sqlalchemy (we have MongoDB and PostgreSQL databases on our backend)
• Understanding Python performance bottlenecks, and how to profile and improve the performance of production code including:
• Optimal multithreading / multiprocessing strategies
• Memory bottlenecks and other bottlenecks encountered with large datasets and use of numpy / opencv / image processing
• Experience in creating soft real-time processing tasks is a plus
• Expertise in Docker-based virtualization including:
• Creating & maintaining custom Docker images
• Deployment of Docker images on cloud and on-premise services
• Experience with maintaining cloud applications in AWS environments
• Experience in deploying machine learning algorithms into production (e.g. PyTorch, tensorflow, opencv, etc) is a plus
• Experience with image processing in python is a plus (e.g. openCV, Pillow, etc)
• Experience with running Nvidia GPU / CUDA-based tasks is a plus (Nvidia Triton, MLFlow)
• Knowledge of video file formats (mp4, mov, avi, etc.), encoding, compression, and using ffmpeg to perform common video processing tasks is a plus.
• Excited about working in a fast-changing startup environment
• Willingness to learn rapidly on the job, try different things, and deliver results
• Ideally a gamer or someone interested in watching gaming content online

Seniority: We are looking for a mid to senior level engineer

Salary: Will be commensurate with experience. 

Who Should Apply:

If you have the right experience, regardless of your seniority, please apply.

Work Experience:  4 years to 8 years

About Sizzle

Sizzle is building AI to automate gaming highlights, directly from Twitch and YouTube videos. Sizzle works with thousands of gaming streamers to automatically create highlights and social content for them. Sizzle is available at www.sizzle.gg. 

Job Title:- Head of Analytics

Job Location:- Bangalore - On - site

About Qrata:

Qrata matches top talent with global career opportunities from the world’s leading digital companies including some of the world’s fastest growing start-ups using qrata’s talent marketplaces. To sign-up please visit Qrata Talent Sign-Up

We are currently scouting for Head of Analytics

Our Client Story:

Founded by a team of seasoned bankers with over 120 years of collective experience in banking, financial services and cards, encompassing strategy, operation, marketing, risk & technology, both in India and internationally.

We offer credit card processing Solution that can help you in effectively managing your credit card portfolio end-to-end. These solution are customized to meet the unique strategic, operational and compliance requirements of each bank.

1. Card Programs built for Everyone Limit assignment based on customer risk assessment & credit profiles including secured cards

2. Cards that can be used Everywhere. Through POS machines, UPI, E-Commerce websites

3. A Card for Everything Enable customer purchases, both large and small

4. Customized Card configurations Restrict usage based on merchant codes, location, amount limits etc

5. End-to-End Support We undertake the complete customer life cycle management right from KYC checks, onboarding, risk profiling, fraud control, billing and collections

6. Rewards Program Management We will manage the entire cards reward and customer loyalty programs for you

What you will do:

We are seeking an experienced individual for the role of Head of Analytics. As the Head of Analytics, you will be responsible for driving data-driven decision-making, implementing advanced analytics strategies, and providing valuable insights to optimize our credit card business operations, sales and marketing, risk management & customer experience. Your expertise in statistical analysis, predictive modelling, and data visualization will be instrumental in driving growth and enhancing the overall performance of our credit card business

Qualification:

• Bachelor's or master’s degree in Technology, Mathematics, Statistics, Economics, Computer Science, or a related field
• Proven experience (7+ years) in leading analytics teams in the credit card industry
• Strong expertise in statistical analysis, predictive modelling, data mining, and segmentation techniques
• Proficiency in data manipulation and analysis using programming languages such as Python, R, or SQL
• Experience with analytics tools such as SAS, SPSS, or Tableau
• Excellent leadership and team management skills, with a track record of building and developing high-performing teams
• Strong knowledge of credit card business and understanding of credit card industry dynamics, including risk management, marketing, and customer lifecycle
• Exceptional communication and presentation skills, with the ability to effectively communicate complex information to a varied audience

What you can expect:

1. Develop and implement Analytics Strategy:

o Define the analytics roadmap for the credit card business, aligning it with overall business objectives

o Identify key performance indicators (KPIs) and metrics to track the performance of the credit card business

o Collaborate with senior management and cross-functional teams to prioritize and execute analytics initiatives

2. Lead Data Analysis and Insights:

o Conduct in-depth analysis of credit card data, customer behaviour, and market trends to identify opportunities for business growth and risk mitigation

o Develop predictive models and algorithms to assess credit risk, customer segmentation, acquisition, retention, and upsell opportunities

o Generate actionable insights and recommendations based on data analysis to optimize credit card product offerings, pricing, and marketing strategies

o Regularly present findings and recommendations to senior leadership, using data visualization techniques to effectively communicate complex information

3. Drive Data Governance and Quality:

o Oversee data governance initiatives, ensuring data accuracy, consistency, and integrity across relevant systems and platforms

o Collaborate with IT teams to optimize data collection, integration, and storage processes to support advanced analytics capabilities

o Establish and enforce data privacy and security protocols to comply with regulatory requirements

4. Team Leadership and Collaboration:

o Build and manage a high-performing analytics team, fostering a culture of innovation, collaboration, and continuous learning

o Provide guidance and mentorship to the team, promoting professional growth and development

o Collaborate with stakeholders across departments, including Marketing, Risk Management, and Finance, to align analytics initiatives with business objectives

5. Stay Updated on Industry Trends:

o Keep abreast of emerging trends, techniques, and technologies in analytics, credit card business, and the financial industry

o Leverage industry best practices to drive innovation and continuous improvement in analytics methodologies and tools

For more Opportunities Visit: Qrata Opportunities.

Job Summary:

We are seeking a highly skilled Enterprise Architect with expertise in Artificial Intelligence (AI), Microservices, and a background in insurance and healthcare to lead our organization's AI strategy, design AI solutions, and ensure alignment with business objectives. The ideal candidate will have a deep understanding of AI technologies, data analytics, cloud computing, software architecture, microservices, as well as experience in the insurance and healthcare sectors. They should be able to translate these concepts into practical solutions that drive innovation and efficiency within our enterprise. Additionally, this role will involve setting up monitoring systems to ensure the performance and reliability of our AI and microservices solutions.

Responsibilities:

AI Strategy Development:

• Collaborate with senior management to define and refine the AI strategy that aligns with the organization's goals and objectives.
• Identify opportunities to leverage AI and machine learning technologies to enhance business processes and create value.

Solution Design:

• Architect AI-driven solutions that meet business requirements, ensuring scalability, reliability, and security.
• Collaborate with cross-functional teams to define system architecture and design principles for AI applications and microservices.
• Evaluate and select appropriate AI technologies, microservices architectures, and frameworks for specific projects.

Data Management:

• Oversee data strategy, including data acquisition, preparation, and governance, to support AI and microservices initiatives.
• Design data pipelines and workflows to ensure high-quality, accessible data for AI models and microservices.

AI Model Development:

• Lead the development and deployment of AI and machine learning models.
• Implement best practices for model training, testing, and validation.
• Monitor and optimize model performance to ensure accuracy and efficiency.

Microservices Architecture:

• Define and implement microservices architecture patterns and best practices.
• Ensure that microservices are designed for scalability, flexibility, and resilience.
• Collaborate with development teams to build and deploy microservices-based applications.

Monitoring Systems:

• Set up monitoring systems for AI and microservices solutions to ensure performance, reliability, and security.
• Implement proactive alerting and reporting mechanisms to identify and address issues promptly.

Integration and Deployment:

• Work with IT teams to integrate AI solutions and microservices into existing systems and applications.
• Ensure seamless deployment and monitoring of AI and microservices solutions in production environments.

Compliance and Security:

• Ensure that AI solutions, microservices, and monitoring systems comply with relevant regulations and data privacy standards.
• Implement security measures to protect AI models, data, and microservices.

Stakeholder Communication:

• Collaborate with business stakeholders to gather requirements and provide regular updates on AI and microservices project progress.
• Translate technical concepts into non-technical language for various audiences.

Research and Innovation:

• Stay up-to-date with emerging AI, microservices, and cloud computing trends, technologies, and best practices.
• Identify opportunities for innovation and propose new AI and microservices initiatives to drive business growth.

Requirements:

• Bachelor's or Masters degree in computer science, Data Science, or a related field.
• Proven experience (X+ years) as an Enterprise Architect with a focus on AI, Microservices, and machine learning.
• Strong knowledge of AI technologies, including deep learning, natural language processing, computer vision, and reinforcement learning.
• Proficiency in data analytics, cloud computing platforms (e.g., AWS, Azure, GCP), big data technologies, and microservices architecture.
• Experience with AI model development, deployment, and monitoring, as well as microservices design and implementation.
• Excellent communication and interpersonal skills.
• Ability to lead cross-functional teams and drive innovation.
• Strong problem-solving and critical-thinking abilities.
• Knowledge of regulatory requirements and data privacy standards related to AI and microservices.

Preferred Qualifications:

• AI-related certifications (e.g., AWS Certified Machine Learning – Specialty, Google Cloud Professional Machine Learning Engineer, etc.).
• Experience in industries such as insurance and healthcare, with a deep understanding of their specific challenges and requirements.
• Previous experience with enterprise architecture frameworks (e.g., TOGAF).

This Enterprise Architect with AI, Microservices, Insurance, and Healthcare Experience role offers an exciting opportunity to shape the AI strategy, microservices architecture, and drive innovation within our organization, particularly in the insurance and healthcare sectors. Additionally, you will play a key role in setting up monitoring systems to ensure the performance and reliability of our AI and microservices solutions. If you have a passion for AI, microservices, and a strong background in these industries, we encourage you to apply and be part of our dynamic team.

Are you passionate about pushing the boundaries of Artificial Intelligence and its applications in the software development lifecycle? Are you excited about building AI models that can revolutionize how developers ship, refactor, and onboard to legacy or existing applications faster? If so, Zevo.ai has the perfect opportunity for you!

As an AI Researcher/Engineer at Zevo.ai, you will play a crucial role in developing cutting-edge AI models using CodeBERT and codexGLUE to achieve our goal of providing an AI solution that supports developers throughout the sprint cycle. You will be at the forefront of research and development, harnessing the power of Natural Language Processing (NLP) and Machine Learning (ML) to revolutionize the way software development is approached.

Responsibilities:

1. AI Model Development: Design, implement, and refine AI models utilizing CodeBERT and codexGLUE to comprehend codebases, facilitate code understanding, automate code refactoring, and enhance the developer onboarding process.
2. Research and Innovation: Stay up-to-date with the latest advancements in NLP and ML research, identifying novel techniques and methodologies that can be applied to Zevo.ai's AI solution. Conduct experiments, perform data analysis, and propose innovative approaches to enhance model performance.
3. Data Collection and Preparation: Collaborate with data engineers to identify, collect, and preprocess relevant datasets necessary for training and evaluating AI models. Ensure data quality, correctness, and proper documentation.
4. Model Evaluation and Optimization: Develop robust evaluation metrics to measure the performance of AI models accurately. Continuously optimize and fine-tune models to achieve state-of-the-art results.
5. Code Integration and Deployment: Work closely with software developers to integrate AI models seamlessly into Zevo.ai's platform. Ensure smooth deployment and monitor the performance of the deployed models.
6. Collaboration and Teamwork: Collaborate effectively with cross-functional teams, including data scientists, software engineers, and product managers, to align AI research efforts with overall company objectives.
7. Documentation: Maintain detailed and clear documentation of research findings, methodologies, and model implementations to facilitate knowledge sharing and future developments.
8. Ethics and Compliance**: Ensure compliance with ethical guidelines and legal requirements related to AI model development, data privacy, and security.

Requirements

1. Educational Background: Bachelor's/Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A strong academic record with a focus on NLP and ML is highly desirable.
2. Technical Expertise: Proficiency in NLP, Deep Learning, and experience with AI model development using frameworks like PyTorch or TensorFlow. Familiarity with CodeBERT and codexGLUE is a significant advantage.
3. Programming Skills: Strong programming skills in Python and experience working with large-scale software projects.
4. Research Experience: Proven track record of conducting research in NLP, ML, or related fields, demonstrated through publications, conference papers, or open-source contributions.
5. Problem-Solving Abilities: Ability to identify and tackle complex problems related to AI model development and software engineering.
6. Team Player: Excellent communication and interpersonal skills, with the ability to collaborate effectively in a team-oriented environment.
7. Passion for AI: Demonstrated enthusiasm for AI and its potential to transform software development practices.

If you are eager to be at the forefront of AI research, driving innovation and impacting the software development industry, join Zevo.ai's talented team of experts as an AI Researcher/Engineer. Together, we'll shape the future of the sprint cycle and revolutionize how developers approach code understanding, refactoring, and onboarding!

We are seeking a talented and motivated AI Verification Engineer to join our team. The ideal candidate will be responsible for the validation of our AI and Machine Learning systems, ensuring that they meet all necessary quality assurance requirements and work reliably and optimally in real-world scenarios. The role requires strong analytical skills, a good understanding of AI and ML technologies, and a dedication to achieving excellence in the production of state-of-the-art systems.

Key Responsibilities:

1. Develop and execute validation strategies and test plans for AI and ML systems, during development and on production environments.
2. Work closely with AI/ML engineers and data scientists in understanding system requirements and capabilities and coming up with key metrics for system efficacy.
3. Evaluate the system performance under various operating conditions, data variety, and scenarios.
4. Perform functional, stress, system, and other testing types to ensure our systems' reliability and robustness.
5. Create automated test procedures and systems for regular verification and validation processes, and detect any abnormal anomalies in usage.
6. Report and track defects, providing detailed information to facilitate problem resolution.
7. Lead the continuous review and improvement of validation and testing methodologies, procedures, and tools.
8. Provide detailed reports and documentation on system performance, issues, and validation results.

Required Skills & Qualifications:

1. Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
2. Proven experience in the testing and validation of AI/ML systems or equivalent complex systems.
3. Good knowledge and understanding of AI and ML concepts, tools, and frameworks.
4. Proficient in scripting and programming languages such as Python, shell scripts etc.
5. Experience with AI/ML platforms and libraries such as TensorFlow, PyTorch, Keras, or Scikit-Learn.
6. Excellent problem-solving abilities and attention to detail.
7. Strong communication skills, with the ability to document and explain complex technical concepts clearly.
8. Ability to work in a fast-paced, collaborative environment.

Preferred Skills & Qualifications:

1.  A good understanding of various large language models, image models, and their comparative strengths and weaknesses.
2. Knowledge of CI/CD pipelines and experience with tools such as Jenkins, Git, Docker.
3. Experience with cloud platforms like AWS, Google Cloud, or Azure.
4. Understanding of Data Analysis and Visualization tools and techniques.

Role: Head of Analytics

Location: Bangalore (Full time)

ABOUT QRATA: 

Qrata matches top talent with global career opportunities from the world’s leading digital companies including some of the world’s fastest growing startups using Qrata’s talent marketplaces. To sign-up, please visit Qrata Talent Sign-Up 

ABOUT THE COMPANY WE ARE HIRING FOR: 

Our client is offering credit card solutions for banks and financial institutions. It provides services like credit card design and onboarding, credit card authorization, payment processing, collections and dispute resolutions, credit card fraud detection, and more. They serve in the B2B space in the FinTech market segments.

POSITION OVERVIEW 

We are seeking an experienced individual for the role of Head of Analytics. As the Head of Analytics, you will be responsible for driving data-driven decision-making, implementing advanced analytics strategies, and providing valuable insights to optimize our credit card business operations, sales and marketing, risk management & customer experience. Your expertise in statistical analysis, predictive modeling, and data visualization will be instrumental in driving growth and enhancing the overall performance of our credit card business.

Responsibilities:

1. Develop and implement Analytics Strategy:

o Define the analytics roadmap for the credit card business, aligning it with overall

business objectives.

o Identify key performance indicators (KPIs) and metrics to track the performance

of the credit card business.

o Collaborate with senior management and cross-functional teams to prioritize and

execute analytics initiatives. 2. Lead Data Analysis and Insights:

o Conduct in-depth analysis of credit card data, customer behavior, and market trends to identify opportunities for business growth and risk mitigation.

o Develop predictive models and algorithms to assess credit risk, customer segmentation, acquisition, retention, and upsell opportunities.

o Generate actionable insights and recommendations based on data analysis to optimize credit card product offerings, pricing, and marketing strategies.

o Regularly present findings and recommendations to senior leadership, using data visualization techniques to effectively communicate complex information.

3. Drive Data Governance and Quality:

o Oversee data governance initiatives, ensuring data accuracy, consistency, and

integrity across relevant systems and platforms.

o Collaborate with IT teams to optimize data collection, integration, and storage

processes to support advanced analytics capabilities.

o Establish and enforce data privacy and security protocols to comply with

regulatory requirements.

4. Team Leadership and Collaboration:

o Build and manage a high-performing analytics team, fostering a culture of innovation, collaboration, and continuous learning.

o Provide guidance and mentorship to the team, promoting professional growth and development.

o Collaborate with stakeholders across departments, including Marketing, Risk Management, and Finance, to align analytics initiatives with business objectives.

5. Stay Updated on Industry Trends:

o Keep abreast of emerging trends, techniques, and technologies in analytics, credit

card business, and the financial industry.

o Leverage industry best practices to drive innovation and continuous improvement

in analytics methodologies and tools.

Qualifications:

Bachelor's or master’s degree in Technology, Mathematics, Statistics, Economics, Computer Science, or a related field.

Proven experience (7+ years) in leading analytics teams in the credit card industry.

Strong expertise in statistical analysis, predictive modelling, data mining, and segmentation techniques.

Proficiency in data manipulation and analysis using programming languages such as Python, R, or SQL.

Experience with analytics tools such as SAS, SPSS, or Tableau.

Excellent leadership and team management skills, with a track record of building and developing high-performing teams.

Strong knowledge of credit card business and understanding of credit card industry dynamics, including risk management, marketing, and customer lifecycle.

Exceptional communication and presentation skills, with the ability to effectively communicate complex information to a varied audience. 

About Kloud9:

Kloud9 exists with the sole purpose of providing cloud expertise to the retail industry. Our team of cloud architects, engineers and developers help retailers launch a successful cloud initiative so you can quickly realise the benefits of cloud technology. Our standardised, proven cloud adoption methodologies reduce the cloud adoption time and effort so you can directly benefit from lower migration costs.

Kloud9 was founded with the vision of bridging the gap between E-commerce and cloud. The E-commerce of any industry is limiting and poses a huge challenge in terms of the finances spent on physical data structures.

At Kloud9, we know migrating to the cloud is the single most significant technology shift your company faces today. We are your trusted advisors in transformation and are determined to build a deep partnership along the way. Our cloud and retail experts will ease your transition to the cloud.

Our sole focus is to provide cloud expertise to retail industry giving our clients the empowerment that will take their business to the next level. Our team of proficient architects, engineers and developers have been designing, building and implementing solutions for retailers for an average of more than 20 years.

We are a cloud vendor that is both platform and technology independent. Our vendor independence not just provides us with a unique perspective into the cloud market but also ensures that we deliver the cloud solutions available that best meet our clients' requirements.

Responsibilities:

●       Studying, transforming, and converting data science prototypes

●       Deploying models to production

●       Training and retraining models as needed

●       Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their respective scores

●       Analyzing the errors of the model and designing strategies to overcome them

●       Identifying differences in data distribution that could affect model performance in real-world situations

●       Performing statistical analysis and using results to improve models

●       Supervising the data acquisition process if more data is needed

●       Defining data augmentation pipelines

●       Defining the pre-processing or feature engineering to be done on a given dataset

●       To extend and enrich existing ML frameworks and libraries

●       Understanding when the findings can be applied to business decisions

●       Documenting machine learning processes

Basic requirements: 

●       4+ years of IT experience in which at least 2+ years of relevant experience primarily in converting data science prototypes and deploying models to production

●       Proficiency with Python and machine learning libraries such as scikit-learn, matplotlib, seaborn and pandas

●       Knowledge of Big Data frameworks like Hadoop, Spark, Pig, Hive, Flume, etc

●       Experience in working with ML frameworks like TensorFlow, Keras, OpenCV

●       Strong written and verbal communications

●       Excellent interpersonal and collaboration skills.

●       Expertise in visualizing and manipulating big datasets

●       Familiarity with Linux

●       Ability to select hardware to run an ML model with the required latency

●       Robust data modelling and data architecture skills.

●       Advanced degree in Computer Science/Math/Statistics or a related discipline.

●       Advanced Math and Statistics skills (linear algebra, calculus, Bayesian statistics, mean, median, variance, etc.)

Nice to have

●       Familiarity with Java, and R code writing.

●       Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world

●       Verifying data quality, and/or ensuring it via data cleaning

●       Supervising the data acquisition process if more data is needed

●       Finding available datasets online that could be used for training

Why Explore a Career at Kloud9:

With job opportunities in prime locations of US, London, Poland and Bengaluru, we help build your career paths in cutting edge technologies of AI, Machine Learning and Data Science. Be part of an inclusive and diverse workforce that's changing the face of retail technology with their creativity and innovative solutions. Our vested interest in our employees translates to deliver the best products and solutions to our customers.

Igeeks is India's no.1 internship platform with 12000+ internships in Engineering, MBA, Commerce & Management, and other streams. Igeeks is offering industrial internships for B.E /Engineering Students based on Embedded Systems / IOT / Machine Learning in Python / Java / Big Data. Electronics and Communication / Computer Science Engineering / Information Science Engineering / Mechanical Engineering / Electrical and Electronics / Telecommunication Engineering Students can Apply For it. Duration of the internship will be 1 Month / 4 weeks. Limited Seats will be offered.

New Internship batch starts from 8th January 2024

Benefits of Internship :

- Work on projects.

- Exposure to work on current technologies

- Company certification

- Hands on experience

For more information refer official website here: www.igeekstechnologies.com

Data Scientist

Cubera is a data company revolutionizing big data analytics and Adtech through data share value principles wherein the users entrust their data to us. We refine the art of understanding, processing, extracting, and evaluating the data that is entrusted to us. We are a gateway for brands to increase their lead efficiency as the world moves towards web3.

What you’ll do?

• Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.
• Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation, and serving.
• Research new and innovative machine learning approaches.
• Perform hands-on analysis and modeling of enormous data sets to develop insights that increase Ad Traffic and Campaign Efficacy.
• Collaborate with other data scientists, data engineers, product managers, and business stakeholders to build well-crafted, pragmatic data products.  
• Actively take on new projects and constantly try to improve the existing models and infrastructure necessary for offline and online experimentation and iteration.
• Work with your team on ambiguous problem areas in existing or new ML initiatives

What are we looking for?

• Ability to write a SQL query to pull the data you need.
• Fluency in Python and familiarity with its scientific stack such as numpy, pandas, scikit learn, matplotlib.
• Experience in Tensorflow and/or R Modelling and/or PyTorch
• Ability to understand a business problem and translate, and structure it into a data science problem. 

Job Category: Data Science

Job Type: Full Time

Job Location: Bangalore

Job Summary

As a Data Science Lead, you will manage multiple consulting projects of varying complexity and ensure on-time and on-budget delivery for clients. You will lead a team of data scientists and collaborate across cross-functional groups, while contributing to new business development, supporting strategic business decisions and maintaining & strengthening client base

1. Work with team to define business requirements, come up with analytical solution and deliver the solution with specific focus on Big Picture to drive robustness of the solution
2. Work with teams of smart collaborators. Be responsible for their appraisals and career development.
3. Participate and lead executive presentations with client leadership stakeholders.
4. Be part of an inclusive and open environment. A culture where making mistakes and learning from them is part of life
5. See how your work contributes to building an organization and be able to drive Org level initiatives that will challenge and grow your capabilities.

​​​​​​Role & Responsibilities

1. Serve as expert in Data Science, build framework to develop Production level DS/AI models.
2. Apply AI research and ML models to accelerate business innovation and solve impactful business problems for our clients.
3. Lead multiple teams across clients ensuring quality and timely outcomes on all projects.
4. Lead and manage the onsite-offshore relation, at the same time adding value to the client.
5. Partner with business and technical stakeholders to translate challenging business problems into state-of-the-art data science solutions.
6. Build a winning team focused on client success. Help team members build lasting career in data science and create a constant learning/development environment.
7. Present results, insights, and recommendations to senior management with an emphasis on the business impact.
8. Build engaging rapport with client leadership through relevant conversations and genuine business recommendations that impact the growth and profitability of the organization.
9. Lead or contribute to org level initiatives to build the Tredence of tomorrow.

Qualification & Experience

1. Bachelor's /Master's /PhD degree in a quantitative field (CS, Machine learning, Mathematics, Statistics, Data Science) or equivalent experience.
2. 6-10+ years of experience in data science, building hands-on ML models
3. Expertise in ML – Regression, Classification, Clustering, Time Series Modeling, Graph Network, Recommender System, Bayesian modeling, Deep learning, Computer Vision, NLP/NLU, Reinforcement learning, Federated Learning, Meta Learning.
4. Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Support Vector Machines ANOVA , Principal Component Analysis, Gradient Boosted Trees, ANN, CNN, RNN, Transformers.
5. Knowledge of programming languages SQL, Python/ R, Spark.
6. Expertise in ML frameworks and libraries (TensorFlow, Keras, PyTorch).
7. Experience with cloud computing services (AWS, GCP or Azure)
8. Expert in Statistical Modelling & Algorithms E.g. Hypothesis testing, Sample size estimation, A/B testing
9. Knowledge in Mathematical programming – Linear Programming, Mixed Integer Programming etc , Stochastic Modelling – Markov chains, Monte Carlo, Stochastic Simulation, Queuing Models.
10. Experience with Optimization Solvers (Gurobi, Cplex) and Algebraic programming Languages(PulP)
11. Knowledge in GPU code optimization, Spark MLlib Optimization.
12. Familiarity to deploy and monitor ML models in production, delivering data products to end-users.
13. Experience with ML CI/CD pipelines.

THE IDEAL CANDIDATE WILL

• Engage with executive level stakeholders from client's team to translate business problems to high level solution approach
• Partner closely with practice, and technical teams to craft well-structured comprehensive proposals/ RFP responses clearly highlighting Tredence’s competitive strengths relevant to Client's selection criteria
• Actively explore the client’s business and formulate solution ideas that can improve process efficiency and cut cost, or achieve growth/revenue/profitability targets faster
• Work hands-on across various MLOps problems and provide thought leadership
• Grow and manage large teams with diverse skillsets
• Collaborate, coach, and learn with a growing team of experienced Machine Learning Engineers and Data Scientists

ELIGIBILITY CRITERIA

• BE/BTech/MTech (Specialization/courses in ML/DS)
• At-least 7+ years of Consulting services delivery experience
• Very strong problem-solving skills & work ethics
• Possesses strong analytical/logical thinking, storyboarding and executive communication skills
• 5+ years of experience in Python/R, SQL
• 5+ years of experience in NLP algorithms, Regression & Classification Modelling, Time Series Forecasting
• Hands on work experience in DevOps
• Should have good knowledge in different deployment type like PaaS, SaaS, IaaS
• Exposure on cloud technologies like Azure, AWS or GCP
• Knowledge in python and packages for data analysis (scikit-learn, scipy, numpy, pandas, matplotlib).
• Knowledge of Deep Learning frameworks: Keras, Tensorflow, PyTorch, etc
• Experience with one or more Container-ecosystem (Docker, Kubernetes)
• Experience in building orchestration pipeline to convert plain python models into a deployable API/RESTful endpoint.
• Good understanding of OOP & Data Structures concepts

Nice to Have:

• Exposure to deployment strategies like: Blue/Green, Canary, AB Testing, Multi-arm Bandit
• Experience in Helm is a plus
• Strong understanding of data infrastructure, data warehouse, or data engineering

You can expect to –

• Work with world’ biggest retailers and help them solve some of their most critical problems. Tredence is a preferred analytics vendor for some of the largest Retailers across the globe
• Create multi-million Dollar business opportunities by leveraging impact mindset, cutting edge solutions and industry best practices.
• Work in a diverse environment that keeps evolving
• Hone your entrepreneurial skills as you contribute to growth of the organization

• NLP 

• ML programming
• Spark
• Model Deployment
• Experience processing unstructured data and building NLP models
• Experience with big data tools pyspark
• Pipeline orchestration using Airflow and model deployment experience is preferred

DATA SCIENTIST-MACHINE LEARNING                           

GormalOne LLP. Mumbai IN

Job Description

GormalOne is a social impact Agri tech enterprise focused on farmer-centric projects. Our vision is to make farming highly profitable for the smallest farmer, thereby ensuring India's “Nutrition security”. Our mission is driven by the use of advanced technology. Our technology will be highly user-friendly, for the majority of farmers, who are digitally naive. We are looking for people, who are keen to use their skills to transform farmers' lives. You will join a highly energized and competent team that is working on advanced global technologies such as OCR, facial recognition, and AI-led disease prediction amongst others.

GormalOne is looking for a machine learning engineer to join. This collaborative yet dynamic, role is suited for candidates who enjoy the challenge of building, testing, and deploying end-to-end ML pipelines and incorporating ML Ops best practices across different technology stacks supporting a variety of use cases. We seek candidates who are curious not only about furthering their own knowledge of ML Ops best practices through hands-on experience but can simultaneously help uplift the knowledge of their colleagues.

Location: Bangalore

Roles & Responsibilities

• Individual contributor
• Developing and maintaining an end-to-end data science project
• Deploying scalable applications on different platform
• Ability to analyze and enhance the efficiency of existing products

What are we looking for?

• 3 to 5 Years of experience as a Data Scientist
• Skilled in Data Analysis, EDA, Model Building, and Analysis.
• Basic coding skills in Python
• Decent knowledge of Statistics
• Creating pipelines for ETL and ML models.
• Experience in the operationalization of ML models
• Good exposure to Deep Learning, ANN, DNN, CNN, RNN, and LSTM.
• Hands-on experience in Keras, PyTorch or Tensorflow

Basic Qualifications

• Tech/BE in Computer Science or Information Technology
• Certification in AI, ML, or Data Science is preferred.
• Master/Ph.D. in a relevant field is preferred.

Preferred Requirements

• Exp in tools and packages like Tensorflow, MLFlow, Airflow
• Exp in object detection techniques like YOLO
• Exposure to cloud technologies
• Operationalization of ML models
• Good understanding and exposure to MLOps

Kindly note: Salary shall be commensurate with qualifications and experience