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Tier-1 brand plus metro Bangalore increases applicant interest, balanced by niche LLM specialization reducing density.
Highly specialized LLM, reinforcement learning, and production ML requirements limit cross-industry transferability.
PhD/Master’s preference and mandatory LLM, RLHF, distributed training, and tooling expertise enforce strict candidate filters.
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Own end-to-end development and deployment of large language models (LLMs) and AI agent systems including training, fine-tuning, evaluation, optimization, and production rollout.
Drive research and implementation of advanced AI capabilities such as reinforcement learning, multi-modal AI, agentic reasoning workflows, and continuous learning pipelines impacting millions of users.
Collaborate cross-functionally with research, engineering, product, and infrastructure teams to deliver scalable, production-grade AI solutions meeting enterprise-grade reliability and efficiency standards.
PhD or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or related field.
Strong hands-on experience in LLM model development, including training, fine-tuning, evaluation, and inference optimization.
Proficiency in Python and experience with deep learning frameworks such as PyTorch or TensorFlow; familiarity with LLM tooling (e.g. Hugging Face, DeepSpeed).
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building and deploying production-scale LLM systems or agentic AI workflows with a focus on reliability, safety, and scalability.
Technically independent contributor with ability to lead complex AI development projects and integrate research innovations into production.
Comfortable working at the intersection of AI research and engineering within fast-paced, iterative environments collaborating across multiple specialized teams.