Sr Data Scientist
Role details
Job location
Tech stack
Job description
Summary: We are seeking a seasoned Senior Data Scientist with overall 10-12 yrs and at least 5-7 years of hands-on experience in developing GenAI/machine learning models and deploying them in a cloud environment, preferably on Google Cloud Platform (GCP). The ideal candidate will design microservice-based solutions, containerize deployments (e.g., GKE), and drive end-to-end SDLC practices. Experience in the pharma domain is a strong advantage., Lead end-to-end development of GenAI/ML models: problem framing, data preparation, model selection, training, evaluation, and iteration.
Architect and implement microservice-based AI solutions and deploy them in containerized environments (preferably GKE); define APIs and data contracts.
Incorporate and operationalize defined ML pipelines with MLOps practices: model versioning, feature stores, experiment tracking, CI/CD for ML, monitoring, and rollback strategies.
Leverage GCP offerings (Vertex AI, BigQuery, Dataflow, Cloud Storage, Pub/Sub, Cloud Run, GKE, etc.) to design scalable AI solutions and efficient data workflows.
Knowledge of Retrieval-Augmented Generation (RAG) concepts and processes
Proficiency with Google Cloud Platform (GCP) and its AI/ML offerings (e.g., Vertex AI, BigQuery, Dataflow, Cloud Storage, GKE).
Deploy, monitor, and maintain models in production; implement observability (logs, metrics, tracing), cost optimization, and performance tuning.
Collaborate with cross-functional teams (data engineers, software engineers, product, regulatory/compliance, analytics) to translate business needs into robust ML solutions.
Uphold SDLC standards: requirements gathering, design, development, testing, deployment, maintenance, and documentation; promote reusable patterns and best practices.
Mentor and guide junior scientists; contribute to code reviews, standards, and knowledge sharing.
Stay current with GenAI advancements and evaluate new tools/approaches; produce reproducible experiments and artifacts.
Requirements
Do you have experience in Model deployment?, Overall 10-12yrs and Minimum 5-7 years of hands-on experience developing GenAI/ML models and deploying them in a cloud environment.