Research Scientist: Agentic AI & Foundation Models

Institute of Foundation Models; Sunnyvale (CA); On-site; USD 150,000 - 450,000; Full time

Benefits offered by this job

Visa sponsorship

Job summary

Institute of Foundation Models is seeking researchers/engineers to advance agentic language models that reason and use tools to complete tasks on a computer. You will contribute to datasets, robust evaluations, and reinforcement learning infrastructure across a broad research-engineering spectrum.

The team seeks depth in algorithmic, empirical, systems, or optimization work, with visa sponsorship available for eligible candidates and a path toward leading-edge foundation model development.

Qualifications

• BS, MS, or PhD degree (or equivalent experience) in Computer Science, Machine Learning, or related fields.
• 2 years of experience in one of: LLM training/fine-tuning, evaluations, reinforcement learning, LLM inference, distributed ML systems.
• Python and PyTorch development experience.
• Experience in using LLM agents for personal or professional use.
• Experience in designing and implementing algorithms from scratch (for algorithms focus).
• Experience in dataset curation and generation (for data focus).
• Experience in building or contributing to training/serving infrastructure (for systems focus).
• Experience in designing and deep diving into evaluations (for evals focus).

Responsibilities

• Propose, prototype, and scale algorithms/systems to support agentic learning
• Develop new paradigms for agentic behavior that go beyond current practices
• Contribute to technical reports, research publications, and open-source software
• Collaborate with other teams to produce state-of-the-art foundation models

Skills

Python

RL concepts

Research mindset

Collaboration

Communication

Education

BS/MS/PhD in CS/ML or related fields

Tools

PyTorch

Ray

Triton

CUDA C++

Job description

Institute of Foundation Models is seeking researchers/engineers to advance agentic language models that reason and use tools to complete tasks on a computer. You will contribute to datasets, robust evaluations, and reinforcement learning infrastructure across a broad research-engineering spectrum.

The team seeks depth in algorithmic, empirical, systems, or optimization work, with visa sponsorship available for eligible candidates and a path toward leading-edge foundation model development.