Staff Engineer, RL Environments & Data Pipelines

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

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