Applied Research Engineer
Technologies
reinforcement learning · post-training · fine-tuning · language models · RL environments · evaluation frameworks · agent systems · forward-deployed
About Applied Compute
Builds 'specific intelligence' AI agents trained from scratch on each enterprise customer's own data, sold to companies like DoorDash, Mercor, and Cognition.
Series A · 10–50 people
Job description
The full responsibilities and requirements are on the employer’s site.
Open application page ↗Source and classification
Production engineering · Evidence for this classification:
The role As an applied research engineer, you’ll own customer engagements end-to-end: understanding their data, their workflows, and their problems, then building and deploying agents that deliver real value. For our largest customers, you'll train custom models tailored to their specific needs. For others, you'll take what you learn and bring it back to improve our general agents. What you'll do Train and post-train models for enterprises, from environment design through deployment Own engagements end-to-end, working directly with technical and business stakeholders Navigate new customer architectures, data systems, and requirements quickly Surface learnings from customers and contribute them back to our platform Collaborate across research, product, and infrastructure to define architectures, evaluation frameworks, and best practices What we're looking for Meaningful AIHow jobs are selected
Employer postings · Data from · Sources