Machine Learning (ML)
Data SciencePrincipal Accountabilities :
1. Good in communication and converting business requirements to functional requirements
2. Develop data-driven insights and machine learning models to identify and extract facts from sales, supply chain and operational data
3. Sound Knowledge and experience in statistical and data mining techniques: Regression, Random Forest, Boosting Trees, Time Series Forecasting, etc.
5. Experience in SOTA Deep Learning techniques to solve NLP problems.
6. End-to-end data collection, model development and testing, and integration into production environments.
7. Build and prototype analysis pipelines iteratively to provide insights at scale.
8. Experience in querying different data sources
9. Partner with developers and business teams for the business-oriented decisions
10. Looking for someone who dares to move on even when the path is not clear and be creative to overcome challenges in the data.
Subodh Popalwar
Software Engineer, Memorres
About Matellio India Private Limited
As an end-to-end web and mobile app development company, we help businesses create robust, IoT, AI/ ML, and Location-based solutions. Get in touch to book a free consultation!
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Data ScienceMachine Learning (ML)Data Scientist – Delivery & New Frontiers Manager
Job Description:
We are seeking highly skilled and motivated data scientist to join our Data Science team. The successful candidate will play a pivotal role in our data-driven initiatives and be responsible for designing, developing, and deploying data science solutions that drives business values for stakeholders. This role involves mapping business problems to a formal data science solution, working with wide range of structured and unstructured data, architecture design, creating sophisticated models, setting up operations for the data science product with the support from MLOps team and facilitating business workshops. In a nutshell, this person will represent data science and provide expertise in the full project cycle. Expectation of the successful candidate will be above that of a typical data scientist. Beyond technical expertise, problem solving in complex set-up will be key to the success for this role.
Responsibilities:
- Collaborate with cross-functional teams, including software engineers, product managers, and business stakeholders, to understand business needs and identify data science opportunities.
- Map complex business problems to data science problem, design data science solution using GCP/Azure Databricks platform.
- Collect, clean, and preprocess large datasets from various internal and external sources.
- Streamlining data science process working with Data Engineering, and Technology teams.
- Managing multiple analytics projects within a Function to deliver end-to-end data science solutions, creation of insights and identify patterns.
- Develop and maintain data pipelines and infrastructure to support the data science projects
- Communicate findings and recommendations to stakeholders through data visualizations and presentations.
- Stay up to date with the latest data science trends and technologies, specifically for GCP companies
Education / Certifications:
Bachelor’s or Master’s in Computer Science, Engineering, Computational Statistics, Mathematics.
Job specific requirements:
- Brings 5+ years of deep data science experience
∙ Strong knowledge of machine learning and statistical modeling techniques in a in a clouds-based environment such as GCP, Azure, Amazon
- Experience with programming languages such as Python, R, Spark
- Experience with data visualization tools such as Tableau, Power BI, and D3.js
- Strong understanding of data structures, algorithms, and software design principles
- Experience with GCP platforms and services such as Big Query, Cloud ML Engine, and Cloud Storage
- Experience in configuring and setting up the version control on Code, Data, and Machine Learning Models using GitHub.
- Self-driven, be able to work with cross-functional teams in a fast-paced environment, adaptability to the changing business needs.
- Strong analytical and problem-solving skills
- Excellent verbal and written communication skills
- Working knowledge with application architecture, data security and compliance team.
Machine Learning (ML)Key Roles/Responsibilities: –
• Develop an understanding of business obstacles, create
• solutions based on advanced analytics and draw implications for
• model development
• Combine, explore and draw insights from data. Often large and
• complex data assets from different parts of the business.
• Design and build explorative, predictive- or prescriptive
• models, utilizing optimization, simulation and machine learning
• techniques
• Prototype and pilot new solutions and be a part of the aim
• of ‘productifying’ those valuable solutions that can have impact at a
• global scale
• Guides and coaches other chapter colleagues to help solve
• data/technical problems at an operational level, and in
• methodologies to help improve development processes
• Identifies and interprets trends and patterns in complex data sets to
• enable the business to take data-driven decisions
Data ScienceMachine Learning (ML)Job Description
We are looking for an experienced engineer to join our data science team, who will help us design, develop, and deploy machine learning models in production. You will develop robust models, prepare their deployment into production in a controlled manner, while providing appropriate means to monitor their performance and stability after deployment.
What You’ll Do will include (But not limited to):
- Preparing datasets needed to train and validate our machine learning models
- Anticipate and build solutions for problems that interrupt availability, performance, and stability in our systems, services, and products at scale.
- Defining and implementing metrics to evaluate the performance of the models, both for computing performance (such as CPU & memory usage) and for ML performance (such as precision, recall, and F1)
- Supporting the deployment of machine learning models on our infrastructure, including containerization, instrumentation, and versioning
- Supporting the whole lifecycle of our machine learning models, including gathering data for retraining, A/B testing, and redeployments
- Developing, testing, and evaluating tools for machine learning models deployment, monitoring, retraining.
- Working closely within a distributed team to analyze and apply innovative solutions over billions of documents
- Supporting solutions ranging from rule-bases, classical ML techniques to the latest deep learning systems.
- Partnering with cross-functional team members to bring large scale data engineering solutions to production
- Communicating your approach and results to a wider audience through presentations
Your Qualifications:
- Demonstrated success with machine learning in a SaaS or Cloud environment, with hands–on knowledge of model creation and deployments in production at scale
- Good knowledge of traditional machine learning methods and neural networks
- Experience with practical machine learning modeling, especially on time-series forecasting, analysis, and causal inference.
- Experience with data mining algorithms and statistical modeling techniques for anomaly detection in time series such as clustering, classification, ARIMA, and decision trees is preferred.
- Ability to implement data import, cleansing and transformation functions at scale
- Fluency in Docker, Kubernetes
- Working knowledge of relational and dimensional data models with appropriate visualization techniques such as PCA.
- Solid English skills to effectively communicate with other team members
Due to the nature of the role, it would be nice if you have also:
- Experience with large datasets and distributed computing, especially with the Google Cloud Platform
- Fluency in at least one deep learning framework: PyTorch, TensorFlow / Keras
- Experience with No–SQL and Graph databases
- Experience working in a Colab, Jupyter, or Python notebook environment
- Some experience with monitoring, analysis, and alerting tools like New Relic, Prometheus, and the ELK stack
- Knowledge of Java, Scala or Go-Lang programming languages
- Familiarity with KubeFlow
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- Experience with OpenCV
About Egnyte
In a content critical age, Egnyte fuels business growth by enabling content-rich business processes, while also providing organizations with visibility and control over their content assets. Egnyte’s cloud-native content services platform leverages the industry’s leading content intelligence engine to deliver a simple, secure, and vendor-neutral foundation for managing enterprise content across business applications and storage repositories. More than 16,000 customers trust Egnyte to enhance employee productivity, automate data management, and reduce file-sharing cost and complexity. Investors include Google Ventures, Kleiner Perkins, Caufield & Byers, and Goldman Sachs. For more information, visit www.egnyte.com
#LI-Remote
Machine Learning (ML)Data Science1.Advanced knowledge of statistical techniques, NLP, machine learning algorithms and deep
learning
frameworks like Tensorflow, Theano, Keras, Pytorch
2. Proficiency with modern statistical modeling (regression, boosting trees, random forests,
etc.),
machine learning (text mining, neural network, NLP, etc.), optimization (linear
optimization,
nonlinear optimization, stochastic optimization, etc.) methodologies.
3. Build complex predictive models using ML and DL techniques with production quality
code and jointly
own complex data science workflows with the Data Engineering team.
4. Familiar with modern data analytics architecture and data engineering technologies
(SQL and No-SQL databases)
5. Knowledge of REST APIs and Web Services
6. Experience with Python, R, sh/bash
Required Skills (Non-Technical):-
1. Fluent in English Communication (Spoken and verbal)
2. Should be a team player
3. Should have a learning aptitude
4. Detail-oriented, analytical and inquisitive
5. Ability to work independently and with others
6. Extremely organized with strong time-management skills
7. Problem Solving & Critical Thinking
Required Experience Level :- Senior level- 4+Years
Work Location : Pune preferred, Remote option available
Work Timing : 2:30 PM to 11:30 PM IST
Data ScienceMachine Learning (ML)Location: Ahmedabad / Pune
Team: Technology
Company Profile
InFoCusp is a company working in the broad field of Computer Science, Software Engineering, and Artificial Intelligence (AI). It is headquartered in Ahmedabad, India, having a branch office in Pune.
We have worked on / are working on AI projects / algorithms-heavy projects with applications ranging in finance, healthcare, e-commerce, legal, HR/recruiting, pharmaceutical, leisure sports and computer gaming domains. All of this is based on the core concepts of data science,
computer vision, machine learning (with emphasis on deep learning), cloud computing, biomedical signal processing, text and natural language processing, distributed systems, embedded systems and the Internet of Things.
PRIMARY RESPONSIBILITIES:
● Applying machine learning, deep learning, and signal processing on large datasets (Audio, sensors, images, videos, text) to develop models.
● Architecting large scale data analytics/modeling systems.
● Designing and programming machine learning methods and integrating them into our ML framework/pipeline.
● Analyzing data collected from various sources,
● Evaluate and validate the analysis with statistical methods. Also presenting this in a lucid form to people not familiar with the domain of data science/computer science.
● Writing specifications for algorithms, reports on data analysis, and documentation of algorithms.
● Evaluating new machine learning methods and adapting them for our
purposes.
● Feature engineering to add new features that improve model
performance.
KNOWLEDGE AND SKILL REQUIREMENTS:
● Background and knowledge of recent advances in machine learning, deep learning, natural language processing, and/or image/signal/video processing with at least 3 years of professional work experience working on real-world data.
● Strong programming background, e.g. Python, C/C++, R, Java, and knowledge of software engineering concepts (OOP, design patterns).
● Knowledge of machine learning libraries Tensorflow, Jax, Keras, scikit-learn, pyTorch. Excellent mathematical skills and background, e.g. accuracy, significance tests, visualization, advanced probability concepts
● Ability to perform both independent and collaborative research.
● Excellent written and spoken communication skills.
● A proven ability to work in a cross-discipline environment in defined time frames. Knowledge and experience of deploying large-scale systems using distributed and cloud-based systems (Hadoop, Spark, Amazon EC2, Dataflow) is a big plus.
● Knowledge of systems engineering is a big plus.
● Some experience in project management and mentoring is also a big plus.
EDUCATION:
- B.E.\B. Tech\B.S. candidates' entries with significant prior experience in the aforementioned fields will be considered.
- M.E.\M.S.\M. Tech\PhD preferably in fields related to Computer Science with experience in machine learning, image and signal processing, or statistics preferred.
Machine Learning (ML)Data Science
PythonKey deliverables for the Data Science Engineer would be to help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be on applying data mining techniques, doing statistical analysis, and building high-quality prediction systems integrated with our products.
What will you do?
- You will be building and deploying ML models to solve specific business problems related to NLP, computer vision, and fraud detection.
- You will be constantly assessing and improving the model using techniques like Transfer learning
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- Assessing the effectiveness and accuracy of new data sources and data gathering techniques.
- Building predictive models and machine-learning algorithms to apply to data sets.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Presenting information using data visualization techniques and proposing solutions and strategies to business challenges
We would love to hear from you if :
- You have 2+ years of experience as a software engineer at a SaaS or technology company
- Demonstrable hands-on programming experience with Python/R Data Science Stack
- Ability to design and implement workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python
- Familiarity with Big Data Platforms (Databricks, Hadoop, Hive), AWS Services (AWS, Sagemaker, IAM, S3, Lambda Functions, Redshift, Elasticsearch)
- Experience in Probability and Statistics, ability to use ideas of Data Distributions, Hypothesis Testing and other Statistical Tests.
- Demonstrable competency in Data Visualisation using the Python/R Data Science Stack.
- Preferable Experience Experienced in web crawling and data scraping
- Strong experience in NLP. Worked on libraries such as NLTK, Spacy, Pattern, Gensim etc.
- Experience with text mining, pattern matching and fuzzy matching
Why Tartan?
- Brand new Macbook
- Stock Options
- Health Insurance
- Unlimited Sick Leaves
- Passion Fund (Invest in yourself or your passion project)
- Wind Down
Deep LearningThe role involves computer vision tasks including development, customization and training of Convolutional Neural Networks (CNNs); application of ML techniques (SVM, regression, clustering etc. ) and traditional Image Processing (OpenCV etc. ). The role is research focused and would involve going through and implementing existing research papers, deep dive of problem analysis, generating new ideas, automating and optimizing key processes.
Requirements:
- 2 - 4 years of relevant experience in solving complex real-world problems at scale via deep learning, computer vision or AI
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- Image Processing techniques using OpenCV or other white-box image feature extraction algorithms.
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serving its customers with one of a kind enterprise HR Chatbot experience. LeenaAI has raised over $35 Mn from top Silicon Valley investors like Bessemer, Greycroft,
YCombinator, Elad Gil etc. Leena is being used by over 2000,000 employees globally in
companies like Coca-Cola, Sony, Tata Technologies, Marico, Vodafone, Cipla etc. and are
growing exponentially fast.
Job Description:
1. Build & Design conversational chatbots that can be directly deployed
for usage by a large volume of customers.
2. Build a training data for our machine learning engine to understand user queries.
3. Build FAQs from company policies.
4. Once system is live, need to debug the negative cases and correct it in the training data
built.
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accuracy.
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Requirements :
1. Adequate verbal communication skills in English. Ability to articulate
the solutions in simple & clear language.
2. Good analytical skills
3. Experience in handling customer queries/worked in chat support
4. Logical knowledge to make control flows.
5. Hands on experience in Microsoft Excel, Microsoft Word
Good to have:
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- We are looking for an experienced data engineer to join our team.
- The preprocessing involves ETL tasks, using pyspark, AWS Glue, staging data in parquet formats on S3, and Athena
To succeed in this data engineering position, you should care about well-documented, testable code and data integrity. We have devops who can help with AWS permissions.
We would like to build up a consistent data lake with staged, ready-to-use data, and to build up various scripts that will serve as blueprints for various additional data ingestion and transforms.
If you enjoy setting up something which many others will rely on, and have the relevant ETL expertise, we’d like to work with you.
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Machine Learning (ML)PythonDeep LearningJob Description:
Roles & Responsibilities:
· You will be involved in every part of the project lifecycle, right from identifying the business problem and proposing a solution, to data collection, cleaning, and preprocessing, to training and optimizing ML/DL models and deploying them to production.
· You will often be required to design and execute proof-of-concept projects that can demonstrate business value and build confidence with CloudMoyo’s clients.
· You will be involved in designing and delivering data visualizations that utilize the ML models to generate insights and intuitively deliver business value to CXOs.
Desired Skill Set:
· Candidates should have strong Python coding skills and be comfortable working with various ML/DL frameworks and libraries.
· Hands-on skills and industry experience in one or more of the following areas is necessary:
1) Deep Learning (CNNs/RNNs, Reinforcement Learning, VAEs/GANs)
2) Machine Learning (Regression, Random Forests, SVMs, K-means, ensemble methods)
3) Natural Language Processing
4) Graph Databases (Neo4j, Apache Giraph)
5) Azure Bot Service
6) Azure ML Studio / Azure Cognitive Services
7) Log Analytics with NLP/ML/DL
· Previous experience with data visualization, C# or Azure Cloud platform and services will be a plus.
· Candidates should have excellent communication skills and be highly technical, with the ability to discuss ideas at any level from executive to developer.
· Creative problem-solving, unconventional approaches and a hacker mindset is highly desired.
Follow CutshortSubodh Popalwar
Software Engineer, Memorres