AI Engineer, RL & Evals

Posted 8 Days Ago
Be an Early Applicant
San Francisco, CA, USA
In-Office
175K-275K Annually
Mid level
Professional Services • Consulting
The Role
Build reinforcement learning environments, evaluation frameworks, agent harnesses, context layers, backend systems, and data pipelines for creative AI applications. Design grading rubrics for subjective domains, collaborate with research teams and frontier AI labs, and ship production infrastructure end to end. The role is fully onsite in San Francisco five days per week.
Summary Generated by Built In

About the company

Our client is a seed-stage AI company building the data and infrastructure layer that improves model quality in subjective, creative domains, starting with design. It has raised $18.5M and has revenue-generating partnerships with frontier AI labs and application-layer companies. Its products support post-training, reinforcement learning, context and verification.

The role

As AI Engineer, RL & Evals, you will build reinforcement learning environments, evaluation frameworks and production infrastructure for creative domains. You will combine backend or full-stack product engineering with applied ML and own systems from design through delivery.

What you'll do

• Build and scale RL environments and evaluation frameworks for creative, non-verifiable domains.

• Design tasks and grading rubrics that capture design quality and taste.

• Build agent harnesses, context layers and supporting product infrastructure.

• Collaborate with internal research teams and frontier labs to improve model output quality.

• Ship production code end to end and build reliable backend systems and data pipelines.


Requirements

What we're looking for

• 2-7 years of relevant AI or reinforcement learning engineering experience, with depth building RL environments, evaluation systems or ML post-training systems.

• Strong full-stack or backend engineering skills and demonstrated production shipping experience.

• Experience with Python, PyTorch, RL, ML evaluation frameworks and LLMs.

• Knowledge of distributed systems and data pipelines; relevant scraping, indexing, embedding or agent-harness work is valuable.

• A computer science degree and fluent English communication.

• Ability to work in the San Francisco office five days per week.

Bonus points

• Experience at creative technology, generative AI, crawling, indexing or data companies.

• Building agentic frameworks or evaluations for non-verifiable domains.

• Experience connecting research work to practical products and infrastructure.


Benefits

Compensation and benefits

• $175,000-$275,000 annual base salary.

• Competitive equity.

Location and work model

Full-time, on-site five days per week in Levi's Plaza, San Francisco, California. Visa transfers, including OPT and H1B transfers, are supported.

Skills Required

  • 2-7 years of relevant AI or reinforcement learning engineering experience
  • Experience building reinforcement learning environments, evaluation systems, or machine learning post-training systems
  • Strong full-stack or backend engineering skills
  • Demonstrated production software shipping experience
  • Experience with Python, PyTorch, reinforcement learning, machine learning evaluation frameworks, and large language models
  • Knowledge of distributed systems and data pipelines
  • Computer science degree
  • Fluent English communication
  • Experience with creative technology, generative AI, crawling, indexing, or data companies
  • Experience building agentic frameworks or evaluations for non-verifiable domains
  • Experience connecting research work to practical products and infrastructure
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The Company
28 Employees
Year Founded: 2021

What We Do

Raydar is a talent acquisition and business consulting firm that connects world-class and emerging talent with growing organizations. It supports companies through team development, strategic hiring, and customized growth solutions, helping clients recruit roles such as engineers, product managers, executives, legal counsel, and quantitative traders. Raydar focuses on understanding each organization’s needs, culture, and long-term goals to build high-impact teams.

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