← All roles

Applied Research - Forward-Deployed

Prime Intellect· Applied Research
Apply on company site
San Francisco, New York$150k - $300kFull-timePosted 8mo ago

About the role

Forward-Deployed Research Engineer embedded with customers to design, implement, and deploy RL-focused evaluation environments, verification harnesses, and deployment recipes on the Lab platform, while feeding field insights back to product and research teams.

Responsibilities

  • Embed directly with strategic customers to understand their agent architectures, failure modes, and product goals
  • Design and build custom RL environments, evaluation harnesses, and verifiers that capture what "good" looks like for each customer's domain
  • Architect agent scaffolding — tool use, multi-step reasoning, memory, sandbox execution — tailored to customer workflows
  • Configure and launch training runs on Lab, iterating on reward functions, rollout strategies, and evaluation criteria
  • Serve as the technical lead for engagements end-to-end: from discovery through deployed, improved models
  • Identify repeatable patterns from customer engagements and codify them into reference implementations, templates, and documentation
  • Serve as the voice of the customer internally, shaping the roadmap for Lab, verifiers, the Environments Hub, and training infrastructure
  • Build high-quality examples and "recipes" that make it easy for new customers and open-source contributors to extend the stack
  • Contribute to technical content (blog posts, tutorials, case studies) that demonstrates real-world platform usage
  • Develop novel evaluation methodologies for agentic behavior — multi-step reasoning, tool use correctness, recovery from failure, long-horizon task completion
  • Prototype and iterate on agent harnesses for real-world tasks: code generation, workflow automation, document processing, and more
  • Experiment with reward design, rubric construction, and environment shaping to improve training signal quality
  • Stay current on the frontier of agentic AI, evals, and post-training methods, and bring that knowledge directly into customer work

Qualifications

  • Deep hands-on experience building, evaluating, or deploying LLM-based agents in the past 1–2 years
  • Strong intuition for evaluation design and rubric development
  • Working understanding of RL and post-training concepts (GRPO, RLHF, reward modeling, SFT)
  • Strong Python skills and familiarity with Hugging Face, inference engines, and agent frameworks
  • Experience in a customer-facing or consulting-adjacent technical role, or as a technical founder
  • Excellent written and verbal communication
  • High agency and comfort with ambiguity

Skills

Required:LLM-based agent developmentEvaluation designPythonRL / post-training conceptsCommunication

Benefits

  • Cash Compensation Range of $150-300k + equity incentives
  • Flexible Work (San Francisco or hybrid-remote)
  • Visa Sponsorship & relocation support
  • Professional Development budget
  • Team Off-sites & conference attendance
Last updated Oct 21, 2026. Interested? Apply on the company site.

About Prime Intellect

Commoditizing Compute & Intelligence

Prime Intellect democratizes AI development at scale. Our platform makes it easy to find global compute resources and train state-of-the-art models through distributed training across clusters. Collectively own the resulting open AI innovations, from language models to scientific breakthroughs.

AI developmentbessemer-ai-infrastructure-2026compute resourcesdistributed trainingmodelsreinforcement-learning-platformsscience
Company profileWebsite

More open roles at Prime Intellect