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Tier-1 brand, metro location, and popular Data Scientist title attract candidates despite niche GenAI requirements.
Core ML/GenAI skills are transferable, but AML/compliance domain specifics raise moderate background sensitivity.
Many mandatory specialized skills (LLMs, RAG, LangChain, MLOps, cloud, Databricks) make filters strict and technical.
Implement generative AI models and advanced solutions for AML transaction monitoring using techniques like RAG, MCP, and LangChain.
Develop and deploy machine learning pipelines to fine-tune large language models and foundation models, integrating AI into production systems with focus on performance, security, and compliance.
Build evaluation frameworks, observability tools, and scalable AI solutions on cloud platforms (AWS, Azure) and data platforms like Databricks.
Strong knowledge and hands-on experience in building and deploying generative AI solutions including LLMs and transformers.
Proficiency in Python and AI/ML frameworks like PyTorch or TensorFlow.
Bachelor's or Master's degree in Computer Science or equivalent.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced with Retrieval-Augmented Generation (RAG) pipelines, Model Context Protocol (MCP), tool calling frameworks, and LangChain/LangGraph for dynamic AI workflows.
Skilled in implementing content generation systems across text, image, and multimodal data and applying computer vision techniques.
Familiar with MLOps practices, cloud platforms (AWS, Azure), Databricks, model evaluation (hallucination detection, bias checks), and integration of AI models into production environments.