Platform Research Engineer
Applied Compute8 months ago
Base Salary
$200k - $335k/yr
Responsibilities
- Build and improve hinting primitives, algorithms, and systems for online self-distillation and continual learning from production traces and company data.
- Develop and maintain trace search, trace mining, and data-labeling systems that support the continual learning loop.
- Research and implement multi-agent system architectures, including agent coordination and trade-off management.
- Build coding agents that automatically create agents for delivery and develop hill-climbing harnesses.
- Translate customer deployment and applied research learnings into generalizable platform features.
- Collaborate with AI product engineers to integrate new ML capabilities into polished platform experiences.
Requirements
- Strong software engineering fundamentals and deep ML/AI knowledge.
- Production research experience involving both training models into production and publishing in top-tier conferences, blogs, or reports.
- Strong experimental design skills and a diligent approach to running experiments.
- Highly organized ability to manage complexity across multiple workstreams.
- Ability to read research papers and translate prototypes into shippable engineering.
- Preferred experience includes reinforcement learning, evaluation frameworks, benchmarks, data quality systems, continual learning, distillation, and multi-agent system architectures.
- Published AI/ML systems work or open-source contributions and previous founder or early-engineer experience are additional advantages.
Benefits
- $200,000–$335,000 U.S. base salary range plus meaningful equity.
- 100% employer-paid health insurance for the employee and family.
- Unlimited PTO and paid parental leave.
- Daily lunches and dinners.
- Transportation and relocation support.
- 5% 401(k) match.
- Full-time role based in the San Francisco Mission office.
- The company sponsors visas and is committed to working through the process with qualified candidates, though success is not guaranteed.
Categories
About Applied Compute
Applied Compute builds enterprise AI systems that turn internal knowledge into custom models and deployable agent workforces. Its platform and forward-deployed teams create evals, train models on proprietary data, and run continually learning agents inside customer environments. The company is privately held and headquartered in San Francisco, serving enterprises that want in-house, domain-specific AI rather than generic foundation models.