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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 employer, mid-level (5-8 yrs), metro location, and popular GenAI role drive high competition.
Specialized GenAI and MLOps skills are transferable, but financial-services preference moderately reduces cross-industry fit.
Explicit 5–8 year requirement plus mandatory GenAI, MLOps, and model-serving expertise enforces high strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Develop, implement, and maintain production-grade generative AI applications end-to-end including data ingestion, model services, deployment, and user interfaces.
Leverage multiple analytical techniques and large complex data sources (structured and unstructured) to generate actionable insights improving client experience and business outcomes.
Own AI product delivery lifecycle including requirements gathering, design, testing, deployment, support, documentation, and collaboration with cross-functional teams.
Minimum Requirements
5-8 years of relevant experience in Data Science, with at least 2 years focused on Generative AI solutions.
Hands-on experience with LLMs and transformer models, prompt engineering, and Retrieval-Augmented Generation (RAG) techniques.
Proficiency with AI/ML frameworks such as PyTorch, TensorFlow, and the Hugging Face ecosystem.
Master's degree preferred in Computer Science or Engineering.
Ideal Candidate Profile
Experienced in launching AI-enabled products in an agile environment, preferably in financial services client experience or operations domain.
Skilled in end-to-end GenAI model customization, MLOps, inference optimization, and quality/safety measures.
Collaborative with strong technical communication skills, able to translate ambiguous business problems into AI-driven solutions across teams.