Member of Technical Staff – Environment Engineering

CGS; San Francisco (CA); On-site; USD 200,000 - 400,000; Full time

Benefits offered by this job

Health, dental and vision insurance

Gym benefits

Meal stipend

Job summary

CGS in San Francisco is seeking a hands-on Member of Technical Staff specializing in Environment Engineering. You will build data pipelines, reinforcement learning environments and evaluation systems alongside AI researchers, transforming real-world tasks into high-quality training data.

This is a fast-paced, on-site startup role requiring immediate availability. You will collaborate with domain experts to design robust data quality checks, graders and evaluation frameworks, and you will own

Qualifications

• Strong programming skills and hands-on experience building data pipelines, automation systems or AI applications.
• Experience in core data delivery, reinforcement learning environments or model evaluation at a data-focused company, or background in quantitative research or trading.
• Ability to investigate data-quality issues in detail and solve problems independently.
• Comfortable working on-site in San Francisco in a demanding startup environment.
• Available to start immediately.

Responsibilities

• Build and ship data pipelines, automation tools and AI applications.
• Develop reinforcement learning environments, datasets and evaluation tasks.
• Collaborate with AI researchers and domain experts to define high-quality training data.
• Design quality checks, evaluation frameworks and graders to measure model performance.
• Identify ambiguous tasks, data-quality issues and opportunities for reward hacking.
• Investigate individual data examples to understand and resolve complex quality issues.
• Take ownership of projects from concept to implementation and validation.

Skills

Programming skills

Data pipelines

Reinforcement learning

AI applications

Problem solving

Tools

Python

TensorFlow/PyTorch

Job description

Member of Technical Staff – Environment Engineering

Location: San Francisco, California, USA (in-office)

Experience: 1+ years

About the Company

Join a fast-growing, seed-stage AI company in San Francisco building data infrastructure and reinforcement learning (RL) environments for AI development. Working with leading AI research labs and enterprise clients across engineering and life sciences, the company has already reached an eight-figure annualised revenue run rate and is scaling rapidly.

With a close-knit team of six aiming to grow to approximately 15 by the end of the year, this is an opportunity to make a direct impact on the future of AI while working alongside leading researchers and experienced founders.

The Role

As a Member of Technical Staff specialising in Environment Engineering, you will build the data pipelines, evaluation systems and reinforcement learning environments that help advance AI capabilities.

You will work directly with AI researchers and domain experts to transform real-world professional work into high-quality training tasks and evaluations. For example, you might connect CAD blueprints with corresponding 3D models to create realistic tasks for AI systems.

This is a hands‑on engineering role for someone who enjoys solving complex problems, building from scratch and working in a fast‑paced startup environment.

Key Responsibilities

• Build and ship data pipelines, automation tools and AI applications.
• Develop reinforcement learning environments, datasets and evaluation tasks.
• Collaborate with AI researchers and domain experts to define high‑quality training data.
• Design quality checks, evaluation frameworks and graders to measure model performance.
• Identify ambiguous tasks, data‑quality issues and opportunities for reward hacking.
• Investigate individual data examples to understand and resolve complex quality issues.
• Take ownership of projects from initial concept through implementation and validation.

Requirements

• At least one year of relevant professional experience, with demonstrable hands‑on technical ability.
• Strong programming skills and experience personally building data pipelines, automation systems or AI applications.
• Experience in core data delivery, reinforcement learning environments or model evaluation at a data‑focused company, or a background in quantitative research or trading.
• A practical, problem‑solving mindset and the ability to investigate data‑quality issues in detail.
• A track record of building and shipping projects independently.
• Comfortable working on‑site in San Francisco, following a demanding 9-9-6 schedule and adapting to a high‑intensity startup environment.
• Available to start immediately.

Candidates with experience in model evaluation, synthetic data, AI agents or reinforcement learning systems are particularly interesting. Personal projects and independently shipped work are also valued.

Candidates from quantitative or trading backgrounds, including those with relevant internships, are encouraged to apply if they can demonstrate strong programming skills and hands‑on technical work.

What's on Offer?

• Competitive base salary of $200,000–$400,000.
• Equity participation of 0.1–0.5%.
• Direct collaboration with leading AI researchers and frontier AI labs.
• The opportunity to help shape a rapidly growing company from an early stage.
• A small, highly technical team with significant individual ownership.
• Health, dental and vision insurance.
• Gym benefits and a $1,000 monthly meal stipend.

Interview Process

• Profile review: Initial assessment by the company's team.
• Technical interview 1: One‑hour whiteboard system‑design interview.
• Technical interview 2: One‑hour open‑ended coding challenge. Candidates may use AI agents, with the focus on their approach and problem‑solving ability.
• On‑site assessment: A full day in the office working on an open‑ended project, followed by a final presentation.
• Offer: Successful candidates proceed to the offer stage.

This position requires working in person in San Francisco, with an immediate start. Visa sponsorship is limited and eligibility depends on the candidate's circumstances. Eligible profiles may include US citizens, green card holders, refugees and asylees, and candidates with qualifying H-1B, O-1 or TN status.