Member of Technical Staff, Research Engineering

True; Mountain View (CA); On-site; USD 200,000 - 300,000; Full time

Job summary

We are seeking an engineer to advance post-training and continual learning for production agents in an early-stage AI company. You will build evaluation suites, run experiments, and transform findings into reliable platform components.

Requirements include 1–5 years of hands-on ML/AI engineering, strong Python, and experience with LLM post-training, evaluation, or inference. On-site in Mountain View, CA with visa sponsorship.

Qualifications

• 1–5 years engineering experience in AI startup or ML research.
• Hands-on with LLM post-training, evaluation or inference.
• Solid Python and CS fundamentals.

Responsibilities

• 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.

Skills

Python

ML foundations

CS fundamentals

LLM post-training

Experiment debugging

Communication

Tools

PyTorch

JAX

Reinforcement learning

vLLM

Megatron

SGLang

Job description

ABOUT THE ROLE

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.

WHAT YOU'LL DO

• 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.

WHAT WE'RE LOOKING FOR

• 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.

COMPENSATION & BENEFITS

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

Visa sponsorship is available.

LOCATION

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