Primeintellect

Applied Research - Forward-Deployed

San Francisco · Exec

Sponsorship not specified$150k-$300kDetected 13 days ago

TypeScriptPythonReactNext.jsFull-Stack DevelopmentDatabricksDatadogMachine LearningLLMsAgentic AILangGraphA/B TestingResearchCommunication

About the role

This is not a traditional research role.
You'll spend most of your time embedded with customers, understanding their models, workflows, and goals.
You are the person who makes the platform work in practice for real workloads.

Design and build custom RL environments, evaluation harnesses, and verifiers that capture what "good" looks like for each customer's domain
Serve as the technical lead for engagements end-to-end: from discovery through deployed, improved models
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
the infrastructure frontier AI labs build internally, made available to every ambitious AI team.
Visa Sponsorship & relocation support
Collaborate with leading researchers, engineers, and partners pushing the boundaries of RL and post-training.
If you're excited to move fast, build boldly, and help define how agentic AI is developed and deployed, we'd love to hear from you.
Ready to build the open superintelligence infrastructure of tomorrow?

Excellent written and verbal communication - you can write a clear environment spec, a compelling case study, and a useful Slack message to a frustrated customer
Experience with agent frameworks and tooling (DSPy, LangGraph, MCP, Stagehand, browser automation)
Research experience - publications, open-source contributions, or benchmarks in ML/RL/agents
Familiarity with sandbox/code execution environments for agent evaluation

Shape the evolution of agent-driven solutions-from research breakthroughs to production systems used by real customers.
Embed directly with strategic customers to understand their agent architectures, failure modes, and product goals
Build high-quality examples and "recipes" that make it easy for new customers and open-source contributors to extend the stack

This listing is sourced directly from Primeintellect's careers page and normalized into a canonical job model.