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Tier-1 brand, metro location, and a mid-level generalist ML/GenAI role attract high competition.
Core ML/GenAI skills are transferable, but consulting and financial-services domain experience increases fit.
Explicit 3–8 years requirement plus hands-on GenAI, ML, and technical tooling makes filters strict.
Design, develop, evaluate, and deploy AI and Generative AI solutions addressing client problems such as knowledge assistants, document intelligence, workflow automation, and decision support.
Translate business problems into AI-enabled approaches, build prototypes, reusable assets, and communicate technical findings to clients.
Ensure responsible AI governance including model risk assessment, privacy, security, compliance, and support practical deployment of AI solutions.
3 to 8 years of experience in AI/ML, data science, GenAI engineering, NLP, advanced analytics, software engineering, or related consulting/analytics roles.
Bachelor's or master's degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, Economics, AI/ML, or related quantitative/technical discipline.
Strong hands-on experience with Python and SQL; knowledge of GenAI concepts including LLMs, transformers, embeddings, prompt engineering, retrieval-augmented generation, fine-tuning, and model evaluation.
Work Experience Required: 3 to 8 years as explicitly mentioned in the JD.
Experienced in building AI/GenAI applications with hands-on skills in Python, SQL, cloud platforms, and modern AI frameworks, and understanding of ML fundamentals.
Able to translate complex client business challenges into scalable AI solutions with a practical, business-impact focus in consulting or client-facing environments.
Familiar with responsible AI governance, including model risk management, privacy, security, auditability, and deployment best practices.