Senior Software Engineer - Task Generation & RL Infrastructure

About The Company

Our company builds RL training data and task construction infrastructure for frontier AI labs. We work with enterprises and health systems to deploy custom AI agents. Founded by teams with deep experience in AI research and agent systems, our company is scaling its task-generation pipeline and agent-deployment business.

About The Role

As a Software Engineer, you'll accelerate task creation for company’s RL training pipeline. The role sits at the intersection of engineering, task design, and system architecture: you'll build internal tools that help contractors generate more tasks at higher quality, construct complex RL environments and tasks yourself, and contribute to custom agent implementations for enterprise customers. This is a specialist role where deep expertise in one domain, whether DevOps, machine learning engineering, systems design, Rust, algorithms, or full-stack architecture, drives real leverage. 5 days a week startup hours either in their office in SF/Palo Alto or remote.

What You'll Own

1. Own task construction: design and build long-horizon, high-difficulty RL tasks that meet company’s specifications within time constraints
2. Build internal tools and infrastructure to help contractors create tasks faster and at higher quality Contribute to custom agent implementations for enterprise customers and health systems
3. Own one core technical domain deeply (DevOps, MLE, systems design, Rust, algorithms, or full-stack) and lead that division of engineering tasks

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4. Ship and iterate on systems that power our core task-generation pipeline

Must-Have

1. At least one year of full-time software engineering experience; open to strong candidates below or above the 1 to 5 year range if they can demonstrate the required depth 
2. Deep, demonstrable excellence in at least one engineering specialty far beyond the general level, such as system design, DevOps, machine learning engineering, Rust, algorithms and optimization, or end-to-end full- stack development 
3. Solid engineering fundamentals alongside the area of specialization 
4. Ability to produce tasks under time constraints, delivering meaningful output within a defined window rather
5. than spending weeks on a single unit 
6. Genuine commitment to a 996 work schedule (9am to 9pm, six days a week); this is a startup-pace role and the expectation is non-negotiable

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 Nice-to-Have

1. Background at a frontier AI research lab, applied ML company, or RL-focused startup 
2. Experience designing or building RL environments, training pipelines, or evaluation systems 
3. Track record shipping production ML systems or infrastructure at scale
4. Competitive programming or algorithmic depth (ACM-ICPC, IOI, or equivalent)
5. Familiarity with containerization, distributed systems, or high-performance computing

Benefits & Perks

1. Equity: 1%
2. Lunch or Dinner in office
3. Health Insurance
4. Bay Club or Equinox membership

Visa Sponsorship: 1 - 5 Years H-1B, OPT