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Niche senior applied AI role requiring LLM and research expertise at a lesser-known employer reduces applicant density.
Core ML research skills are transferable, though enterprise AI experience favors candidates from similar industries.
Requires deep ML/LLM expertise, demonstrable PoCs, research pedigree, and leadership, making filters highly selective.
Lead technical applied AI research from ambiguous business problems to structured experimentation and validated proofs-of-concept.
Own formulation of hypotheses, experimentation design, alternative solution evaluation, and producing implementation-ready technical handoffs for development.
Collaborate closely with cross-functional teams including business stakeholders, AI engineers, data engineers, cloud architects, and product teams to ensure solution viability and readiness.
Proven experience translating business/customer problems into applied AI solutions with hands-on experimentation and PoC development.
Strong knowledge of machine learning, deep learning, generative AI, LLMs, RAG, agentic AI; proficiency in Python and modern ML/AI frameworks.
Experience collaborating with software engineering, data, cloud, architecture, or product teams and communicating technical trade-offs to technical and non-technical audiences.
Work Experience Required: Not explicitly mentioned in the JD; Location: Hyderabad, India; On-site role.
Demonstrated ability to operate at the intersection of business problem discovery, AI research, and solution architecture with measurable results (e.g., evaluated PoCs, credible AI solutions).
Experience in rapidly evolving research and innovation environments with established methodologies for applied AI research and experimentation.
Track record of building technical credibility and mentoring junior researchers or AI engineers while driving high-value technical ownership.