Research Engineer / Research Scientist - Palo Alto, CA, United States

Originally posted 14 May 2026 by the employer.

About the role

This role involves designing and training foundation models that power personal AI, focusing on architectures that continuously learn, deeply personalize, and run efficiently on local hardware. You will take ownership of the research lifecycle from ideating novel algorithms to scaling large training runs.

What you'll do

• Design, train, and evaluate novel foundation models optimized for reasoning, multimodal understanding, and personalization.
• Conduct research in continual learning to enable real-time model adaptation based on local user interaction without catastrophic forgetting.
• Develop techniques for data efficiency, alignment (such as RLHF), and parameter-efficient fine-tuning (PEFT) targeting bespoke personal hardware.
• Collaborate with the infrastructure team to scale and unblock experimental architectures across compute clusters.

What you'll need

• BS, MS, or Ph.D. in Computer Science, Machine Learning, Mathematics, or equivalent practical industry experience.
• Understanding of modern deep learning architectures (including Transformers and diffusion models) and advanced training methodologies.
• Hands-on experience with PyTorch or JAX, with a track record of writing scalable code for model training.
• Demonstrated ability to take open-ended research problems from mathematical formulation to working, scaled implementations.

Nice to have

• Record of publications at AI conferences (such as NeurIPS, ICLR, or ICML) or equivalent industry research breakthroughs.
• Expertise in continual learning, reinforcement learning, or optimizing models for edge/on-device inference.
• Experience pre-training or aligning frontier-scale language or multimodal models.