TrustIn
About the Role
As a Member of Technical Staff, you’ll work across the stack – from low-level systems to higher-level product flows – to build:
Rich RL environments and realistic simulated data sets.
Representative tasks and evals that encode complex real-world goals.
The infrastructure layer (compute, orchestration, storage, observability) that makes all of this scalable and reliable.
You’ll collaborate directly with founders, researchers, and other senior engineers, and you’ll regularly delegate and coordinate work executed by fleets of coding agents and tools.
Requirements
Location: San Francisco or New York – predominantly in-office. Compensation: $200k–$600k + competitive equityType: Full-time, permanent
What You’ll Do
Design and implement production-grade simulation and RL environments used by internal and external teams.
Build systems for generating and managing large volumes of realistic synthetic data.
Develop and maintain the core infrastructure: job schedulers, cluster orchestration, storage, experiment tracking, monitoring, and deployment pipelines.
Work closely with AI researchers to turn prototypes into robust, repeatable systems.
Write clear technical design docs, review proposals, and drive projects from idea → implementation → rollout.
Participate in on-call and incident response for the systems you own.
What We’re Looking For
Strong background in software engineering (full-stack or infrastructure), with clear ownership of complex systems in production.
Deep comfort with at least one of:
Low-level infrastructure (distributed systems, networking, performance engineering, OS/runtime internals), or
Being an early/founding engineer on a technically demanding product.
Proficiency in one or more of: Python, Go, Rust, C++, or similar systems languages.
Experience with cloud compute and orchestration (e.g. Kubernetes, Ray, Slurm, custom clusters).
Ability to move quickly while maintaining high engineering standards: profiling, testing, code review, observability.
Genuine interest in AI research, RL, and agentic systems, even if you’re primarily an infra person.
High agency: you’re comfortable with ambiguity, own problems end-to-end, and bias to action.
(Years of experience are flexible; we care more about depth, ownership, and trajectory than a specific number.)
Nice to Have
Experience building or scaling RL environments, simulators, or game engines.
Background working with frontier AI models, evals, or safety tools.
Prior experience in a small, high-intensity startup or research lab environment.
Why This Role
You’re working at the frontier of AI systems every day, directly enabling advanced agents to interact with rich, realistic environments.
Small team, large surface area – your work touches research, infra, and customer-facing use cases.
Compensation and equity aligned with top-tier AI and infra companies.
About the Company
We’re an applied AI research and engineering company working with leading labs, hyperscalers, and large enterprises. Our focus is building realistic simulation environments and evaluation frameworks that help advanced agents learn, reason, and act safely in the real world.
We’re small, deeply technical, and moving fast. The work sits right at the edge of AI research and heavy-duty infrastructure.