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Strong Tier-1 brand and metro locations increase competition despite niche senior ML research focus.
High because role requires deep ML research background, publications, and specialized agentic AI expertise.
High due to explicit 9+ years, advanced degree, research publication and deep ML specialization requirements.
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Lead foundational research in agentic AI and intelligent systems focusing on novel modeling and learning approaches beyond prompt engineering or LLM assembly.
Develop new algorithms, model architectures, and training methodologies to improve AI agents' reasoning, planning, memory, tool use, and long-horizon task performance.
Drive rigorous experimentation to validate research and translate advances into product, including leading technical reviews and mentoring junior ML engineers.
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.
Demonstrated research expertise in areas such as Large Language Models, generative modeling, NLP, computer vision, multimodal learning, representation learning, reinforcement learning, or reasoning and planning.
Strong fundamentals in machine learning, deep learning, optimization, statistical modeling, and programming skills with modern deep learning frameworks.
Experienced in formulating novel ML research problems and experimentally validating new approaches with measurable impact and publications.
Able to integrate foundational AI domains (e.g., LLMs, generative models, multimodal learning) towards advancing agentic intelligence systems.
Capable of technical leadership including conducting design reviews, mentoring engineers, and collaborating cross-functionally to translate research into production features.