Job Description 3+ years of work experience in Python programming for AI/ML, deep learning, and Generative AI model development Proficiency in TensorFlow/PyTorch, Hugging Face Transformers and Langchain libraries Hands-on experience with NLP, LLM prompt design and fine-tuning, embeddings, vector databases and agentic frameworks Strong understanding of ML algorithms, probability and optimization techniques 6+ years of experience in deploying models with Docker, Kubernetes, and cloud services (AWS Bedrock, SageMaker, GCP Vertex AI) through APIs, and using MLOps and CI/CD pipelines Familiarity with retrieval-augmented generation (RAG), cache-augmented generation (CAG), retrieval-integrated generation (RIG), low-rank adaptation (LoRA) fine-tuning Ability to write scalable, production-ready ML code and optimized model inference Experience with developing ML pipelines for text classification, summarization and chat agents Prior experience with SQL and noSQL databases, and Snowflake/Databricks

Experience in setting up data pipelines in Azure. Experience with Azure Data Factory Experience with setting up Azure Data Lake with structured/unstructured data. Candidate needs to be a self-starter and should be able to design, develop and deliver solution without much assistance or supervision. Strong knowledge of Azure services - Storage (AFS, Blob, Data Lake), Azure Functions. Strong knowledge of database - Should be able to write complex queries, schema design. Ability to set up CI/CD pipelines in Azure through GitHub. Qualifications Bachelor s or master s degree in computer science, Information Technology Experience with batch job scheduling and identifying data/job dependencies. Preferred Skills: Proficiency in data warehousing, ETL, and big data processing. Familiarity with the Pharma domain is a plus.