Research Engineer​/Scientist Efficient Models San Jose Regular

Research Engineer/Scientist (all levels), Efficient Models

Location:

San Jose

• Take initiatives in designing and implementing efficient models for large‑scale generative AI, with emphasis on large model distillation and compression.
• Develop efficient algorithms and architectures for large‑scale generative and multimodal models using techniques such as step distillation, cfg distillation, quantization, and other methods.
• Advance scalable generative modeling approaches, including diffusion and autoregressive models, with focus on acceleration and efficiency.
• Contribute to distillation frameworks, model acceleration, hardware‑efficient inference, and their applications.
• Develop methods and infrastructure for transferring capabilities from foundation models into smaller, more efficient models.

• B.S. in Computer Science or related field, or equivalent experience.
• Expertise in efficient models with deep understanding of computational bottlenecks and acceleration methods.
• Proficiency in training generative AI or LLM models using PyTorch and JAX.
• Strong communication and collaboration skills in fast‑paced environments.

• Ph.D. in GenAI, MLSys or equivalent experience.
• Extensive research experience in broad GenAI, MLSys, LLM areas.
• Proven experience in at least one of: image/video generation and editing; model compression (quantization, step/cfg distillation); efficient architectures (MoE, window attention); efficient model design; or reinforcement learning training methods (RLHF, DPO, GRPO).

Base salary range: $156,000 – $387,600 annually.