VP of AI Algorithms Research — Scale, Theory & Impact

Aumni; New York (NY); Presencial; USD 180.000 - 250.000; Jornada completa

Descripción de la vacante

JPMorgan Chase & Co. is seeking an AI Algorithms Research Scientist, Vice President, to advance algorithmic foundations for large-scale AI. You will develop novel algorithms, implement them efficiently, and contribute to IP protections while collaborating with internal teams and presenting at conferences.

The role requires a PhD and 2+ years of experience in AI/ML theory or optimization, with strong Python/C++/CUDA skills and a track record of high-quality research and publications.

Formación

• Ph.D. with at least 2 years of experience in AI/ML, optimization, or theory.
• Proficiency in Python and C/C++ or CUDA for performance-critical work.
• Experience developing performant codes and strong scientific writing.
• Excellent communication and ability to present to non-technical audiences.
• Experience in one or more domains: efficient learning/inference, optimization, scaling laws, hardware–algorithm co-design.

Responsabilidades

• Advance algorithmic foundations of large-scale AI for model training, inference, and agentic systems.
• Develop novel algorithms to improve accuracy, latency, and compute cost.
• Establish theoretical grounding including convergence and sample efficiency.
• Implement algorithms in performant software and validate at scale.
• Provide research solutions to internal project teams and document findings for papers.
• Contribute to JPMorgan Chase IP protections of generated IP.

Conocimientos

AI/ML research

Optimization theory

Python

C/C++/CUDA

Communication

Publications

Educación

PhD in CS/Math/Physics/EE/Statistics

Herramientas

CUDA

Triton

Nsight

PyTorch

Descripción del empleo

JPMorgan Chase & Co. is seeking an AI Algorithms Research Scientist, Vice President, to advance algorithmic foundations for large-scale AI. You will develop novel algorithms, implement them efficiently, and contribute to IP protections while collaborating with internal teams and presenting at conferences.

The role requires a PhD and 2+ years of experience in AI/ML theory or optimization, with strong Python/C++/CUDA skills and a track record of high-quality research and publications.