Member of Technical Staff, Research Engineering

Join an early-stage AI company developing specialized models and learning systems for production agents. You will work across research and production engineering, building post-training methods and infrastructure that improve model quality, cost, and latency in real-world applications.

• Build evaluation suites, graders, and data pipelines using production workflows and traces.
• Own post-training projects in customer settings, including data work, evaluations, reinforcement learning environments, and training runs.
• Implement agent environments and harnesses for reproducible experiments and training data generation.
• Run and analyze post-training experiments, reproduce promising research, and debug related systems.
• Turn successful experiments into reliable components of a post-training and continual learning platform.

• One to five years of engineering experience at an AI startup or in an ML research group, working hands-on with LLM post-training, evaluation, or inference.
• Strong Python programming skills and solid foundations in machine learning and computer science.
• Hands‑on experience training, evaluating, and serving LLMs, beyond using APIs or prompt and agent wrappers.
• Experience with tools and technologies such as PyTorch, JAX, reinforcement learning, agent environments, evaluation harnesses, vLLM, SGLang, or Megatron.
• Evidence of building and owning technical work, such as shipped systems, engineering internships, open‑source contributions, research, or substantial projects.
• Ability to learn unfamiliar systems, debug independently, communicate technical decisions, and measure whether solutions work.

Base salary: $200,000 to $300,000 annually.

Visa sponsorship is available.

On‑site, five days per week in Mountain View, California.