Member of Technical Staff, Research Engineering

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

Benefits offered by this job

Visa sponsorship

Job summary

True Talent Solutions Partners in Mountain View, CA, offers an on-site role building post-training methods for AI systems. You will span research and production, developing evaluation suites, data pipelines, and reproducible training environments.

The ideal candidate has 1–5 years in AI startup or ML research, strong Python and ML fundamentals, and hands-on experience with LLM post-training, evaluation, or inference. Visa sponsorship is available.

Qualifications

• 1–5 years of engineering experience in AI startup or ML research group.
• Hands-on experience with LLM post-training, evaluation, or inference.
• Ability to learn unfamiliar systems and debug independently.

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 fundamentals

Experimentation

Communication

Tools

PyTorch

JAX

Megatron

vLLM

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.