AI-ML_EMAI0120PS at EnterpriseMinds · Remote only · 5 - 8 years · ₹8L - ₹22L / yr · Profitable · Remote only · Posted 20 Jan 2023

cutting-edge technology to problems that have never been solved before, working with architecture and
product teams to collaboratively visualize, design and create machine learning models for M3LD- the
world’s first privacy platform that helps users get control of their data and enterprises to establish trustbased relationships.
KEY ACCOUNTABILITIES & ACTIVITIES
AI-ML Software
Engineer
Accountabilities
& Activities
▪ Study and transform data science prototypes
▪ Design machine learning systems
▪ Research and implement appropriate ML algorithms and tools
▪ Develop machine learning applications according to requirements
▪ Select appropriate datasets and data representation methods
▪ Run machine learning tests and experiments
▪ Perform statistical analysis and fine-tuning using test results
▪ Train and retrain systems when necessary
▪ Extend existing ML libraries and frameworks
▪ Keep abreast of developments in the field
BACKGROUND, SKILLS & QUALIFICATIONS
Knowledge,
Skills and
Experience
▪ Ability and passion to deliver extraordinary results with minimal direction
▪ Collaborating with teams to dissect complex problems and design solutions tailored to M3LD
needs
▪ Expertise in big data processing, data pipeline, machine learning, and AI processing methods.
▪ Proficiency in programming languages - e.g. Python, Java, C++, Ruby.
▪ Track-record of shipping and maintaining code in production with a commitment to high quality,
well-tested code, and automation
▪ Experience with object-oriented design, multi-threading, and synchronisation
▪ Experience with ML frameworks and libraries (Spark, tensor, OpenAI)
▪ Ability to optimize runtime with performant data structures, leveraging distributed systems and/or
cloud platforms
▪ Excellent written skills and ability to document system design documentations.
▪ Experience working in “agile” development environment and collaboration tools like Jira,
Confluence, etc.
▪ Ability to communicate effectively with cross project stakeholders both verbally and in writing
▪ Ability to collaborate with distributed teams across time zones
Qualifications ▪ 5+ years of relevant work experience in enterprise, mobile and complex solution development,
and software engineering
▪ Strong computer science fundamentals required
▪ Experience with deep learning frameworks.
▪ Strong experience in programming and statistics.
▪ Experience working with DevOps practices, Git version control, and agile development
approaches.
▪ Experience developing for major cloud platforms, including Azure, AWS, Google Cloud, and
Oracle Cloud Infrastructure is preferred.

About EnterpriseMinds
About
Enterprise Minds, with core focus on engineering products, automation and intelligence, partners customers on the trajectory towards increasing outcomes, relevance and growth.
Harnessing the power of Data and the forces that define AI, Machine Learning and Data Science, we believe in institutionalising go-to-market models and not just explore possibilities.
We believe in a customer-centric ethic without and people-centric paradigm within. With a strong sense of community, ownership and collaboration our people work in a spirit of co-creation, co-innovation and co-development to engineer next-generation software products with the help of accelerators.
Through Communities we connect and attract talent that shares skills and expertise. Through Innovation Labs and global design studios we deliver creative solutions.
We create vertical isolated pods which has narrow but deep focus. We also create horizontal pods to collaborate and deliver sustainable outcomes.
We follow Agile methodologies to fail fast and deliver scalable and modular solutions. We constantly self-asses and realign to work with each customer in the most impactful manner.
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Job Description:
We are seeking a highly skilled Machine Learning Engineer to join our team. The ideal candidate will have a strong background in Natural Language Processing (NLP), Large Language Models (LLMs), and Python programming.
You will work closely with data scientists, product managers, and data engineers to design, develop, and deploy high-performance AI/ML models and integrate generative AI solutions into existing workflows.
Your responsibilities will include:
- Collaborating with cross-functional teams to design and deliver high-performance AI models, including NLP, computer vision, semantics engines, linguistic analysis, risk management, and time-series prediction models. Integrating generative AI solutions into existing workflow systems.
- Developing and maintaining the ML Operations CI/CD pipeline for seamless deployment and monitoring. Training, tuning, and optimizing AI models and algorithms for enhanced performance.
- Implementing complex real-time data and AI/ML applications to capture knowledge and automate decision-making processes.
- Creating ML/AI models for business teams and establishing metrics to track their accuracy and performance. Overseeing the full lifecycle of algorithm development, from ideation to deployment and monitoring. Evaluating and ranking ML algorithms based on their potential success in solving specific problems.
- Serving as an internal resource for AI/ML needs, providing guidance and insights to stakeholders during strategic discussions.
Required Experience and Skills:
Machine Learning:
- Proficient in generative AI techniques, prompt engineering, and Retrieval-Augmented Generation (RAG) (3+ years).
- Experience with Large Language Models (LLMs) such as OpenAI, Gemini, LLAMA, and other state-of-the-art models (3+ years).
- Expertise in using ML/AI libraries such as Pandas, NumPy, PyTorch, TensorFlow, Keras, BERT, LayoutLM, and traditional ML algorithms (5+ years).
- Experience with distributed ML/AI training libraries/models: Koalas, Horovod, DDP.
Python Programming and Software Engineering:
- Expertise in Pythonic clean coding practices, including the use of decorators, generators, and descriptors (5+ years).
- Strong understanding of software design principles such as DRY, OAOO, YAGNI, KIS, EAFP/LBYL, and defensive programming (2+ years).
- Proficient in software design concepts focusing on cohesion and coupling (2+ years). Knowledge of SOLID principles (2+ years).
Education and Experience:
- Minimum Bachelor's degree or foreign equivalent in Computer Science, Electrical Engineering, or a closely related field.
- At least 5 years of experience as a software engineer and 5 years of ML-related programming.
Sr Engineer – Artificial Intelligence
Job Summary
As an AI Engineer at Emerson, you will be responsible for analysing complex data sets to
identify trends, develop predictive models, and provide actionable insights. You will work closely
with cross-functional teams to understand business needs and deliver data-driven solutions that
enhance decision-making and drive business growth.
In This Role, Your Responsibilities Will Be:
Analyze large, complex data sets using statistical methods and machine learning
techniques to extract meaningful insights.
Develop and implement predictive models and algorithms to solve business problems
and improve processes.
Create visualizations and dashboards to effectively communicate findings and insights to
stakeholders.
Work with data engineers, product managers, and other team members to understand
business requirements and deliver solutions.
Clean and preprocess data to ensure accuracy and completeness for analysis.
Prepare and present reports on data analysis, model performance, and key metrics to
stakeholders and management.
Participate in regular Scrum events such as Sprint Planning, Sprint Review, and Sprint
Retrospective
Stay updated with the latest industry trends and advancements in data science and
machine learning techniques.
For This Role, You Will Need:
Bachelor’s degree in computer science, Data Science, Statistics, or a related field or a
master's degree or higher is preferred.
Total 5-7 years of industry experience
More than 3 years of experience in a data science or analytics role, with a strong track
record of building and deploying models.
Proficiency in programming languages such as Python or R, and experience with data
manipulation libraries (e.g., pandas, NumPy).
Excellent understanding of Agentic Frameworks like Microsoft Agent Framework.
Experience with NLP, NLG, and Large Language Models Open Source as well as Cloud
based models.
Experience with SQL and NoSQL databases such as MongoDB, Cassandra, Vector
databases
Experience with Dockers, Asynchronous Data Orchestrators, environments etc.
Strong analytical and problem-solving skills, with the ability to work with complex data
sets and extract actionable insights.
Excellent verbal and written communication skills, with the ability to present complex
technical information to non-technical stakeholders.
Preferred Qualifications that Set You Apart:
Prior experience in engineering domain would be nice to have
Prior experience in working with teams in Scaled Agile Framework (SAFe) is nice to
have
Possession of relevant certification/s in data science from reputed universities
specializing in AI.
Familiarity with cloud platforms, Microsoft Azure is preferred
Ability to work in a fast-paced environment and manage multiple projects simultaneously.
Strong analytical and troubleshooting skills, with the ability to resolve issues related to
model performance and infrastructure.
AI/ML Engineer AI Operating System for Capital Markets Location Bangalore/Chennai Experience 5+ years Function Artificial Intelligence / Machine Learning Employment Type About Transient.AI Full-time Transient.AI is building a next-generation AI Operating System for capital markets — a unified intelligence layer that connects research, trading, compliance, and sales functions at banks and hedge funds. Today, these teams largely operate on disconnected legacy systems, forcing manual, expensive workarounds. Transient.AI replaces that fragmentation with a single AI-native layer built for institutional-grade compliance, security, and auditability. The company already has live products in market, including Caddie.AI (a research automation tool that cuts hedge fund research time significantly), ClarityRIA (helping sales teams identify the right investors in seconds), and CapFlo.AI (automated parsing of complex derivatives contracts). Founded by former traders and technologists from Goldman Sachs, Credit Suisse, UBS, and McKinsey, Transient.AI is headquartered in New York, with teams in Miami, Singapore, and India. The company has raised Series A funding and is scaling its engineering and product organization globally. Role Overview Transient.AI is hiring an experienced AI/ML Engineer to join its India engineering team in Bangalore/Chennai. This is a hands-on, build-from-scratch role — you'll be designing and shipping the core machine learning systems that power the company's flagship products, working closely with founders and senior engineers rather than inheriting existing infrastructure. Key Responsibilities • Design, build, and deploy machine learning and AI models that power Transient.AI's core products (research automation, document intelligence, investor matching, and workflow orchestration). • Workonapplied NLP/LLMsystems, including retrieval-augmented generation, structured extraction from unstructured financial documents, and model evaluation pipelines. • Partner closely with product and founding engineers to translate capital markets workflows into scalable AI systems. • Ownmodelperformance, reliability, and cost — from experimentation through production deployment. • Build and maintain data pipelines, feature stores, and evaluation frameworks to support rapid iteration. • Ensuresystems meet the compliance, auditability, and security standards required in regulated financial environments. What We're Looking For • 5+years ofexperience building and deploying machine learning or AI systems in production.• Strong hands-on experience with Python and modern ML/AI frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, or equivalent). • Experience with LLMs — fine-tuning, prompt engineering, RAG architectures, or agentic systems — is highly valued. • Solid grounding in data structures, distributed systems, and MLOps practices (model serving, monitoring, versioning). • Prior experience at a strong product company, high-growth startup, or a top-tier engineering background • Comfort operating in an early-stage, high-ownership environment with limited process and high ambiguity. • Exposure to fintech, capital markets, or other regulated industries is a plus, though not mandatory. WhyJoin Transient.AI • Build core AI systems from the ground up — not maintain legacy code. • Workdirectly with founders who have deep, first-hand Wall Street experience (Goldman Sachs, Credit Suisse, UBS, McKinsey). • JoinaSeries A-funded company solving a real, expensive problem for institutional finance. • Bepart ofasmall, global team with outsized ownership and impact. .
About the Role
We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, MLOps, and Generative AI. The ideal candidate will have hands-on experience in building scalable ML models, deploying them in production, and working with modern AI frameworks, including GenAI technologies.
Key Responsibilities
· Design, develop, and deploy machine learning models for real-world business problems
· Work on end-to-end ML lifecycle: data preprocessing, model building, evaluation, deployment, and monitoring
· Implement and manage MLOps pipelines for scalable and reproducible workflows
· Utilize tools like MLflow for experiment tracking, model versioning, and lifecycle management
· Develop and integrate Generative AI (GenAI) solutions such as LLM-based applications
· Collaborate with cross-functional teams (engineering, product, business) to translate requirements into AI solutions
· Optimize model performance and ensure production stability
· Stay updated with the latest advancements in AI/ML and GenAI ecosystems
Required Skills & Qualifications
· 4+ years of experience in Data Science / Machine Learning
· Strong programming skills in Python
· Hands-on experience with ML modeling techniques (supervised, unsupervised, NLP, etc.)
· Solid understanding of MLOps practices and tools
· Experience with MLflow or similar model lifecycle tools
· Practical experience in Generative AI (GenAI), including working with LLMs
· Experience with libraries/frameworks like Scikit-learn, TensorFlow, PyTorch
· Strong understanding of data structures, algorithms, and statistics
· Experience with cloud platforms (AWS/GCP/Azure) is a plus
Good to Have
· Experience with LLM fine-tuning, prompt engineering, or RAG pipelines
· Exposure to Docker, Kubernetes, and CI/CD pipelines
· Knowledge of data engineering workflows
Key Responsibilities
• Design, build, and deploy machine learning and AI models that power Transient.AI's core products (research
automation, document intelligence, investor matching, and workflow orchestration).
• Work on applied NLP/LLM systems, including retrieval-augmented generation, structured extraction from
unstructured financial documents, and model evaluation pipelines.
• Partner closely with product and founding engineers to translate capital markets workflows into scalable AI
systems.
• Own model performance, reliability, and cost — from experimentation through production deployment.
• Build and maintain data pipelines, feature stores, and evaluation frameworks to support rapid iteration.
• Ensure systems meet the compliance, auditability, and security standards required in regulated financial
environments.
What We're Looking For
• 5+ years of experience building and deploying machine learning or AI systems in production.• Strong hands-on experience with Python and modern ML/AI frameworks (PyTorch, TensorFlow, Hugging Face,
LangChain, or equivalent).
• Experience with LLMs — fine-tuning, prompt engineering, RAG architectures, or agentic systems — is highly
valued.
• Solid grounding in data structures, distributed systems, and MLOps practices (model serving, monitoring,
versioning).
• Prior experience at a strong product company, high-growth startup, or a top-tier engineering background
• Comfort operating in an early-stage, high-ownership environment with limited process and high ambiguity.
• Exposure to fintech, capital markets, or other regulated industries is a plus, though not mandatory
Job Summary/ Job Opportunity:
This is an excellent opportunity for an ideal candidate with a high level of technical proficiency and meeting the below mentioned criteria -- • Strong experience in Machine Learning, Deep Learning, Generative AI, and Large Language Models (LLMs). • Hands-on experience building and deploying production-grade solutions using Azure OpenAI, OpenAI, LangChain, LangGraph, Semantic Kernel, LlamaIndex, and Agentic AI frameworks. • Strong expertise in Python, API development, microservices, and cloud-native architectures. • Experience designing and implementing RAG solutions, vector databases, embeddings, knowledge retrieval systems, and AI copilots. • Experience with Azure cloud services, MLOps, CI/CD pipelines, monitoring, and model lifecycle management. • Strong understanding of AI governance, responsible AI, security, compliance, and model evaluation frameworks. • Ability to lead technical discussions, provide architectural recommendations, mentor team members, and interact with business stakeholde
Key Objectives and Major Responsibilities:
• Design, develop, and implement scalable AI/ML and Generative AI solutions for enterprise applications. • Lead development of intelligent applications leveraging LLMs, RAG pipelines, AI agents, and document intelligence solutions. • Collaborate with business stakeholders, architects, and product teams to translate business requirements into technical solutions. • Design and optimize data pipelines, vector search solutions, embeddings, and retrieval mechanisms. • Build and maintain REST APIs, microservices, and cloud-native AI applications. • Ensure best practices in coding standards, performance optimization, security, scalability, and maintainability. • Drive AI solution deployment using MLOps practices, CI/CD pipelines, monitoring, and observability frameworks. • Perform code reviews, mentor junior developers, and contribute to capability building within the team
Key Capabilities and Competencies:
Knowledge, Skills, Qualification and Experience
• Degree in B.Tech/M.Tech (Computer Science/IT/Data Science) or related discipline preferred, with 3–4 years of relevant experience in AI/ML, GenAI and total 5-7 years of experience. • Proficiency in Python and hands-on experience with ML libraries (scikit-learn, TensorFlow, PyTorch) and GenAI frameworks/tools. • Strong understanding of machine learning, deep learning, LLMs, prompt engineering, and techniques like RAG and fine-tuning. • Experience with data processing, embeddings, vector databases, APIs, and building scalable AI driven applications. • Good communication skills, ability to work on multiple projects, and eagerness to learn and adapt to evolving AI technologies.
Principal Software Engineer
Company Summary :
As the recognized global standard for project-based businesses, Deltek delivers software and information solutions to help organizations achieve their purpose. Our market leadership stems from the work of our diverse employees who are united by a passion for learning, growing and making a difference. At Deltek, we take immense pride in creating a balanced, values-driven environment, where every employee feels included and empowered to do their best work. Our employees put our core values into action daily, creating a one-of-a-kind culture that has been recognized globally. Thanks to our incredible team, Deltek has been named one of America's Best Midsize Employers by Forbes, a Best Place to Work by Glassdoor, a Top Workplace by The Washington Post and a Best Place to Work in Asia by World HRD Congress. www.deltek.com
Position Responsibilities :
About the Role
We are seeking a highly motivated AI Solutions Engineer to join Deltek’s growing AI Center of Excellence team to design, develop, deploy, and optimize internal Artificial Intelligence and Machine Learning solutions that solve complex business challenges. The ideal candidate combines deep expertise in AI, machine learning, Generative AI, Large Language Models (LLMs), SLMs, software engineering, cloud computing, and MLOps/LLMOps to build scalable, production-grade AI applications.
The AI Solutions Engineer will collaborate with AI data scientists, architects, and engineering teams to deliver innovative AI-driven solutions while ensuring security, scalability, governance, and operational excellence. This role reports to the Senior AI Solutions Architect.
Key Responsibilities
AI & Machine Learning Development
- Design, build, train, evaluate, and deploy machine learning and deep learning models.
- Develop Generative AI solutions using Large Language Models (LLMs) such as GPT, Claude, Gemini, Llama, and Mistral.
- Implement Retrieval-Augmented Generation (RAG), prompt engineering, fine-tuning, and AI agent frameworks.
- Build NLP, recommendation systems, forecasting, predictive analytics, and intelligent automation solutions.
- Optimize model performance, scalability, latency, and cost.
Software Engineering & Solution Development
- Develop production-grade AI applications using Python and modern software engineering practices.
- Build APIs, microservices, and AI-powered enterprise applications.
- Integrate AI services with enterprise systems, business applications, and data platforms.
- Apply coding standards, automated testing, CI/CD, and version control best practices.
MLOps & AI Operations
- Design and implement MLOps pipelines for model development, deployment, monitoring, and lifecycle management.
- Automate model training, validation, testing, and deployment processes.
- Monitor model performance, data drift, hallucinations, and operational metrics.
- Support continuous improvement and reliability of AI platforms.
Cloud & Platform Engineering
- Develop AI solutions on Azure, AWS, or Google Cloud platforms.
- Leverage cloud-native AI services, containerization, Kubernetes, and serverless technologies.
- Build scalable architectures supporting enterprise AI workloads and real-time inference.
AI Governance & Security
- Ensure compliance with Responsible AI, security, privacy, and regulatory requirements.
- Implement model governance, explainability, bias mitigation, and risk management practices.
- Maintain standards for secure design, deployment, and operation of AI solutions.
Required Qualifications
Education
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related technical field.
Experience
- 5+ years of software engineering or machine learning development experience.
- 2+ years of hands-on experience developing and deploying Agentic AI, Generative AI or AI/ML solutions in production environments.
Technical Skills
Programming & Engineering
- Strong expertise in Python.
- Experience with Java, ReactJS, JavaScript, or similar programming languages.
- Solid understanding of algorithms, data structures, APIs, and software design principles.
Artificial Intelligence & Machine Learning
- Machine Learning and Deep Learning concepts and frameworks.
- Model training, evaluation, optimization, and deployment.
Generative AI
- Large Language Models (LLMs) & SLMs
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- AI Agents and Agentic Workflows
- Fine-tuning and model customization
- Vector embeddings and semantic search
Frameworks & Tools
- PyTorch, TensorFlow, Scikit-learn
- LangChain, LlamaIndex, Semantic Kernel, MCP, A2A and Transformers
- FastAPI, Flask
Data & Analytics
- SQL and NoSQL databases
- Data pipelines, ETL, and data modeling
- Experience with AWS, Azure and Google
MLOps & DevOps
- MLflow, Kubeflow, Azure ML, SageMaker
- Docker and Kubernetes
- Git, GitHub, Azure DevOps, Jenkins
- CI/CD automation and model monitoring
Cloud Platforms
- AWS (preferred)
- AWS Bedrock or Azure OpenAI Service
- AWS SageMaker
- Google Vertex AI
Preferred Qualifications
- Experience designing enterprise-scale AI platforms and products.
- Knowledge of multi-agent architectures and autonomous AI systems.
- Experience with vector databases such as Pinecone, Snowflake Cortex, Pgvector, Weaviate, Chroma, or Azure AI Search.
- Understanding of AI governance, compliance, and Responsible AI frameworks.
- Relevant certifications in Azure AI, AWS Machine Learning, or Google Cloud AI.
ML DEVELOPER
Hyperworks Imaging is a cutting-edge technology company based out of Bengaluru, India since 2016. Our team uses the latest advances in deep learning and multi-modal machine learning techniques to solve diverse real world problems. We are rapidly growing, working with multiple companies around the world.
JOB OVERVIEW
We are seeking a talented and results-oriented ML Developer to join our growing team in India. In this role, you will be responsible for developing and implementing new advanced ML algorithms and AI agents for creating AI assistants of the future.
The ideal candidate will work on a complete ML pipeline starting from extraction, transformation and analysis of data to developing novel ML algorithms. The candidate will implement latest research papers and closely work with various stakeholders to ensure data-driven decisions and integrate the solutions into a robust ML pipeline.
RESPONSIBILITIES:
- Create AI agents using Model Context Protocols (MCPs), Claude Code, DsPy etc.
- Develop custom evals for AI agents.
- Build and maintain ML pipelines
- Optimize and evaluate ML models to ensure accuracy and performance.
- Define system requirements and integrate ML algorithms into cloud based workflows.
- Write clean, well-documented, and maintainable code following best practices
REQUIREMENTS:
- 2-3+ years of experience in data science, machine learning, or a similar role.
- Demonstrated expertise with python, PyTorch, and TensorFlow.
- Graduated/Graduating with B.Tech/M.Tech/PhD degrees in Electrical Engg./Electronics Engg./Computer Science/Maths and Computing/Physics
- Has done coursework in Linear Algebra, Probability, Image Processing, Deep Learning and Machine Learning.
- Has demonstrated experience with Model Context Protocols (MCPs), DSPy, AI Agents, MLOps etc
WHO CAN APPLY:
Only those candidates will be considered who,
- have relevant skills and interests
- can commit full time
- Can show prior work and deployed projects
- can start immediately
Please note that we will reach out to ONLY those applicants who satisfy the criteria listed above.
SALARY DETAILS: Commensurate with experience.
JOINING DATE: Immediate
JOB TYPE: Full-time
Job Title: Senior AI/ML Engineer
Company: Timble Technologies Pvt. Ltd
Location: Gurugram (Hybrid)
Experience: 2 TO 5 Years
About Us
Timble Glance is a high-growth AI RegTech and B2B SaaS company catering to top-tier BFSI and enterprise clients. We build cutting-edge systems powering 30+ high-scale APIs for digital identity verification, fraud detection, document intelligence, and compliance automation.
Role Overview
We are looking for a hands-on Senior AI/ML Engineer to design, develop, and productionize high-throughput AI/ML and Generative AI systems. You will own the full lifecycle—from problem formulation and data pipelines to deep learning architectures, RAG systems, LLMOps, and model governance—delivering sub-second latency and high reliability across our enterprise products.
Key Responsibilities
· Model Architecture & Deployment: Design, train, and deploy production-scale ML/Deep Learning and GenAI systems (computer vision, document intelligence, OCR, NLP, fraud risk classification, and LLM applications).
· GenAI & LLM Solutions: Develop robust LLM workflows including prompt engineering, fine-tuning, RAG pipelines, semantic search, vector indexing (Pinecone/Milvus/Chroma), and safety guardrails.
· Pipelines & Engineering: Build performant feature extraction and data pipelines; write modular, vectorized, production-grade Python (NumPy, Pandas) and advanced SQL.
· MLOps & Monitoring: Establish end-to-end MLOps/LLMOps standards—model registries, CI/CD, experiment tracking, drift detection, A/B testing, latency optimization, and cost governance.
· Responsible AI & Security: Ensure model decisions comply with enterprise data security, privacy standards, and auditability required by the BFSI sector.
· Collaboration & Ownership: Translate complex business requirements into technical roadmaps, conduct rigorous code reviews, and mentor junior engineers.
Required Qualifications & Skills
· Education: B.Tech / M.Tech in Computer Science, AI/ML, Mathematics, or a related field—Tier-1 institutes (IIT, IIIT, NIT) strongly preferred.
· Experience: 2+ years of hands-on experience developing, deploying, and maintaining ML/Deep Learning or GenAI models in production environments.
· GenAI & NLP Stack: Hands-on experience with LLMs, embeddings, RAG architectures, and frameworks such as LangChain, LlamaIndex, or Hugging Face.
· Deep Learning Frameworks: Strong proficiency in PyTorch or TensorFlow, with deep knowledge of transformer architectures and modern NLP/CV models.
· Software & Data Engineering: Expert-level Python skills (pytest, Git, OOP, asynchronous programming), solid SQL proficiency, and familiarity with data workflows.
· Deployment & Cloud: Practical exposure to cloud platforms (AWS/GCP), containerization (Docker), API frameworks (FastAPI/Flask), and basic orchestration (Kubernetes).
Preferred Qualifications
· Prior domain experience in Fintech, RegTech, Identity Verification (KYC/AML), Fraud Intelligence, or B2B SaaS.
· Experience optimizing models for low latency and inference cost (e.g., ONNX, TensorRT, model quantization).
· Familiarity with workflow orchestrators such as Airflow, Prefect, or Kubeflow.
About Nexora Group
Nexora Group is a technology and innovation-driven organization dedicated to building intelligent solutions that leverage Artificial Intelligence, Machine Learning, Data Analytics, and emerging technologies. We are committed to fostering talent by providing aspiring professionals with practical exposure, mentorship, and opportunities to work on real-world projects.
Internship Overview
Nexora Group is looking for enthusiastic and driven AI/ML Interns to join our team. This internship is ideal for students and recent graduates who are passionate about Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI. Interns will gain hands-on experience working on real-world AI projects, developing intelligent models, and solving complex business challenges using data-driven approaches.
Key Responsibilities
- Assist in developing, training, and evaluating Machine Learning models.
- Collect, clean, and preprocess datasets for AI/ML applications.
- Conduct exploratory data analysis and feature engineering.
- Work on Deep Learning, Natural Language Processing (NLP), and Computer Vision projects.
- Research and implement AI algorithms and emerging technologies.
- Support the development of Generative AI and Large Language Model (LLM)-based solutions.
- Optimize model performance and evaluate results using industry-standard metrics.
- Document project workflows, findings, and technical reports.
- Collaborate with cross-functional teams to develop innovative AI solutions.
Required Skills
- Basic understanding of Machine Learning and Artificial Intelligence concepts.
- Knowledge of Python programming.
- Familiarity with libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, or Keras.
- Understanding of data structures, algorithms, and statistics.
- Basic knowledge of Deep Learning, NLP, or Computer Vision concepts.
- Strong analytical and problem-solving skills.
- Good communication and teamwork abilities.
- Willingness to learn and adapt to new technologies.
Preferred Qualifications
- Experience with AI/ML projects, hackathons, or research work.
- Knowledge of Generative AI, Prompt Engineering, and LLMs.
- Familiarity with cloud platforms and AI deployment tools.
- Certifications in AI, Machine Learning, or Data Science are a plus.
- GitHub projects or portfolio showcasing AI/ML work.
Eligibility
- Undergraduate or postgraduate students pursuing Computer Science, Artificial Intelligence, Machine Learning, Data Science, Information Technology, or related fields.
- Recent graduates seeking practical industry experience.
- Candidates with a strong interest in AI innovation and research.
What You'll Gain
- Hands-on experience with real-world AI and Machine Learning projects.
- Mentorship from experienced AI professionals.
- Exposure to cutting-edge AI tools, frameworks, and technologies.
- Internship Completion Certificate.
- Letter of Recommendation based on performance.
- Opportunity for a Pre-Placement Offer (PPO) for outstanding performers.
- Professional networking and career development opportunities.







