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Tier-1 brand plus metro locations increase candidate density despite the niche research focus.
Requires deep ML research experience and publication track record, limiting cross-industry transferability.
Explicit 9+ years, advanced degree and strong publication/research requirements create strict filtering.
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Lead foundational research to advance AI agents' reasoning, planning, learning, memory, tool use, and long-horizon task performance.
Develop and experimentally validate novel model architectures, learning algorithms, and training/inference methodologies to improve agentic AI capabilities.
Translate research breakthroughs into product-ready solutions and lead rigorous experimentation and prototyping efforts.
9+ years of hands-on machine learning engineering experience in industry or research.
MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, or related field with significant industry or research experience.
Strong fundamentals in machine learning, deep learning, optimization, and statistical modeling.
Demonstrated research expertise in at least one of: large language models, generative modeling, computer vision, multimodal learning, representation learning, reinforcement learning, or reasoning/planning.
Experienced research scientist with strong publication record and ability to formulate and solve novel ML research problems.
Deep expertise and strategic fit in generative modeling, LLMs, multimodal learning, or reinforcement learning directly connected to agentic AI systems.
Comfortable leading technical design reviews, mentoring junior engineers, and collaborating cross-functionally to translate research into products.