Senior AI/ML Engineer Job in Bangalore at Takeda

Takeda is hiring for the role of Senior AI/ML Engineer!

Responsibilities of the Candidate:

• Act as a trusted advisor and an internal Gen AI consultant to functional stakeholders and internal Takeda Business Units and Business Functions for data science activities.
• Serve as a Lead for Gen AI use cases and operationalization on complex projects with diverse scope, including primary contact for internal liaison with Global Data, Team, and other parts of the GDD&T and BU/BF functions.
• Designed and built RAG service platform orchestrations, including prompt engineering, guardrails, vector databases, and API Grounding.
• Design, develop, and implement MLOps pipelines for Generative AI models, covering data ingestion, preprocessing, training, deployment, and monitoring.
• Automate ML tasks using GitOps, CI/CD pipelines, and containerization tools like Docker and Kubernetes.
• Creates database-to-deployment pipelines for models using the necessary programming languages (primarily R, Python, SQL) and tools (AWS SageMaker, Dataiku, Databricks, etc.). This is a hands-on role; you must code 50%-70% of your time.
• Acts as central steward of data quality monitor risks through the holistic review of clinical and operational data, uses detailed knowledge of the protocol

Requirement

• Overall 5+ years of experience in data, business insights, and ML experience in Life Sciences, primarily in commercial (sales, marketing, medical, and access) functions.
• For a master's or a PhD, a minimum of 3 years of Machine Learning or Data Science experience in Technology companies, Life Sciences, Pharma, or Biotech is expected.
• Experience with Generative AI, including transformers or LLM project work with frameworks, including Huggingface, LangChain, or GPT
• 2+ years of experience applying large language and generative AI models, including transformers and GPT models.
• Experience in building chatbots, retrieval augmented generation, and finetuning LLMs.
• Experience building production-grade ML/automation pipelines from scratch (model versioning, lineage, monitoring, deployment, optimization, scalability, orchestration, and continuous learning).
• Proficient in Python, SQL, Git, and Jenkins and in frameworks such as sci-kit-learn, Keras, PyTorch, Tensorflow, etc.
• Experience in using MLOps frameworks like Kubeflow, MLFlow, and DataRobot.
• Experience with DataBricks, Dataiku AWS SageMaker, Azure, and data pipeline management tools like Airflow.
• Minimum 3 years of experience automating ML build, training, evaluating, and deploying ML models.
• Minimum 3 years of experience designing and implementing cloud solutions (AWS, Azure, or GCP).