Research Engineer / Research Scientist
Hybrid (Palo Alto)$200k - $420kPosted 2mo ago
About the role
Research role at River focused on designing and training foundation models for personal AI, with emphasis on continual learning, personalization, and efficient on-device inference on bespoke hardware.
Responsibilities
- Design, train, and evaluate novel foundation models optimized for reasoning, multimodal understanding, and extreme personalization.
- Pioneer research in continual learning, enabling models to adapt in real-time based on local user interaction without catastrophic forgetting.
- Develop advanced techniques for data efficiency, alignment (e.g., RLHF), and parameter-efficient fine-tuning (PEFT) targeting bespoke personal hardware.
- Partner directly with the infrastructure team to rapidly scale and unblock experimental architectures across large compute clusters.
Qualifications
- BS, MS, or Ph.D. in Computer Science, Machine Learning, Mathematics, or equivalent practical industry experience.
- Deep understanding of modern deep learning architectures (e.g., Transformers, diffusion models) and advanced training methodologies.
- Extensive hands-on experience with PyTorch or JAX, with a track record of writing clean, scalable code for model training.
- Proven ability to take open-ended research problems from mathematical formulation to working, scaled implementations.
- A highly collaborative mindset and a bias for action to push boundaries in a fast-paced environment.
Skills
Required:foundation modelscontinual learningdata efficiency
Nice to have:RLHF / alignmentPEFTon-device inference
Benefits
- Comprehensive health, dental, and vision insurance; unlimited PTO; relocation assistance as needed.
Last updated Sep 23, 2026. Interested? Apply on the company site.
About River AI
Intelligence that flows with you
River is building a new stack for Personal AI.
LoRA fine-tuningReinforcement learningOpen modelsPay per tokenAPIPersonal AI
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