Applied Research Engineer

Responsibilities

• Own technical deployment requests from frontier AI labs, data vendors, and internal teams from triage to completion
• Ask the right questions to clarify ambiguous asks and identify what actually needs to be done
• Build tools and one-off pipelines to solve urgent customer or partner problems
• Coordinate with research and GTM teams to unblock deployments
• Balance speed and quality in situations where customers need fast turnaround and the path is not fully specified
• Document recurring issues and turn repeated manual work into reusable tools or processes

Requirements

• Proficiency in Python, Docker, and Linux environments
• Experience working on benchmarks and evals - you can reason about what makes a task realistic, a rubric reliable, an environment usable, and a trajectory useful for RL training
• Strong debugging instincts across code, data, and environments
• Demonstrated ability to operate independently in ambiguous situations without a fully prescribed roadmap
• Strong judgment about when to move fast, when to escalate, and when correctness or security requires extra care
• Comfort working directly with technical customers, vendors, or cross-functional internal teams

Nice-to-Haves

• Experience in applied research engineering or forward-deployed engineering
• Experience handling urgent production, customer, or deployment issues
• Early-stage startup experience with ability to work independently in fast-paced environments
• Strong communication skills for remote collaboration across time zones

We prioritize technical aptitude and learning potential over years of experience.