Reinforcement Learning Engineer
Posted 18 Dec 2025
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 3+ yrs
- Management level
- Individual contributor
- Employment
- On-Site
- Contract
- Full-time
No salary listed for this role.
Field of studyComputer Science, Operations Research, Robotics (or related)
Study levelMaster's or higher
About Hammerhead
We're unleashing AI with intelligent orchestration while addressing one of the most pressing bottlenecks for AI access to Power. Our cutting-edge platform optimizes data center power infrastructure to maximize AI token generation within existing electrical limits, without requiring new power plants or grid expansions. Our team has optimized over 8 gigawatts of mission-critical power globally, and we're addressing a $64 billion-per-year market opportunity while dramatically reducing the environmental footprint of AI infrastructure.
At Hammerhead, you will:
⚡ Work at the intersection of AI, energy, and compute creating the next generation AI infrastructure
🤝 Collaborate with colleagues that are experts in modern RL and AI, IoT and IIoT software, and infrastructure technologies
🌎 Contribute to building a more efficient and sustainable future for AI compute.
🚀 Join a company at the cutting edge of modern data center design and operation
💰 Receive competitive compensation, equity, and benefits in a high-growth, mission-driven environment.
🚀Learn from an experienced team that has built and sold startups before
Learn more about Hammerhead
Role Description
As a Reinforcement Learning Engineer, you will be the architect of the core intelligence for Hammerhead’s ORCA platform. Reporting to the Head of AI / Reinforcement Learning Engineering, you will design, train, and deploy the Orchestrated RL Control Agents that form the brain of our system, making real-time decisions to optimize power and compute resources across physical data centers. This role is for a hands-on expert who is passionate about applying cutting-edge RL research to complex, real-world industrial systems. You will be instrumental in developing the models that control physical assets like cooling systems and power distribution units to unlock massive efficiency gains in AI workloads.
Key Responsibilities
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RL Model Development: Design and implement advanced reinforcement learning algorithms (e.g., multi-agent RL, model-based RL, deep RL) for real-time control of data center infrastructure.