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Senior AI Research Scientist (Generative Models)

NeuralDynamics AI
San Francisco
Salary Estimate
USD 225.000 – USD 315.000
Live Update
11 Mei 2026
Deadline
11 Mei 2027

Job Description

NeuralDynamics is at the forefront of the generative revolution. We are looking for a visionary Senior AI Research Scientist to architect the next generation of Large Language Models (LLMs) and multimodal systems. In this role, you will work alongside world-class researchers and engineers to push the boundaries of what is possible in machine intelligence, focusing on scalability, reasoning, and real-world alignment. You will have access to massive compute clusters and proprietary datasets to turn theoretical breakthroughs into industrial-scale reality.

Responsibilities

  • Lead the research and development of novel transformer architectures and efficient training methodologies.
  • Optimize large-scale distributed training runs across thousands of H100 GPUs using DeepSpeed and Megatron-LM.
  • Collaborate with product teams to integrate cutting-edge research into production-ready AI features that impact millions.
  • Publish high-impact research papers at top-tier conferences like NeurIPS, ICML, or ICLR to maintain company thought leadership.
  • Develop innovative fine-tuning techniques including RLHF, DPO, and PEFT to improve model alignment and reasoning capabilities.
  • Mentor junior researchers and engineers, fostering a culture of technical excellence and rapid iteration.

Qualifications

  • PhD in Computer Science, Mathematics, or a related quantitative field with a primary focus on Deep Learning.
  • Proven track record of high-impact research in NLP, Computer Vision, or Multimodal Generative AI.
  • Expert-level proficiency in Python and deep learning frameworks such as PyTorch or JAX.
  • Hands-on experience with distributed systems and high-performance computing (HPC) environments.
  • Strong mathematical foundation in linear algebra, calculus, and probability theory.
  • Ability to translate complex theoretical concepts into efficient, scalable, and maintainable code.

Required Skills

PyTorch LLMs Distributed Training Transformers NLP Reinforcement Learning CUDA JAX

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