Lead Data Scientist

Responsibilities:

• Application Design: Take ownership for services within the team to ensure its launch, improvement and maintenance and participate in product design discussion and decisions.
• Collaboration: Partner with various stakeholders to make data driven decisions and formulate overall data strategy and work with the data science & engineering teams to establish and follow organizational best practices.
• Leadership: Bring technical guidance and thought leadership within the team and conduct technical reviews. Provide mentorship and training to junior team members.
• Execution: Enhance current product features and proactively develop new features which have a reasonable value proposition for the end-user and suggest improvements and optimizations in deployed algorithms.
• Research: Stay up-to-date with the latest research in Machine Learning - Generative AI, NLP, Computer Vision, Audio Processing, Knowledge Graphs, Recommendation Systems and MLOps to drive innovation.
• Agile: Ability to work and juggle priorities to thrive in a fast paced and ambiguous environment, while also collaborating as part of a team in complex situations.
• Monitor: Analyze relevant KPIs, KRAs to make informed design choices, aiming for optimal cost, performance, user experience, and business outcomes.

Requirements:

• B.Tech / M.Tech from a top-tier engineering college in Computer Science, Mathematics, or a related field.
• 5+ years of experience in Machine Learning and Engineering and 2+ years of experience in effectively managing and leading teams.
• Strong problem solving skills and readiness to learn new concepts and apply them to find practical solutions to complex problems.
• Strong foundational concept and knowledge of concepts in Statistics and Machine Learning, including Linear/Logistic regression, SVM, Random Forest, Boosting, Clustering, Approximate Nearest Neighbour, Neural Networks, NLP, Computer Vision, Transformer Models, LLM, Generative AI etc.
• Experience with Machine Learning libraries and tools ( Pytorch / TensorFlow, HuggingFace, Nvidia Triton, TorchServe etc.) and Python programming using Flask-uWSGI-Celery.
• Track record of implementing and deploying systems and maintaining them in production environments.
• Experience using, designing and developing microservices, associated APIs and Event driven queue systems, with a thorough understanding of REST, gRPC, GraphQL.
• Strong experience in DevOps principles, IaC and related best practices (CI/CD, Docker, Kubernetes, Application Monitoring, Logging).
• Bonus: Prior experience with AWS services (ECS, S3, SNS, Sagemaker, OpenSearch) and familiarity with platforms like (MLFlow, Kubeflow) for managing ML lifecycle and experimentation.