Reinforcement Learning Engineer

Reinforcement Learning Engineer – Hammerhead

AI, Inc.

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, addressing a $64 billion‑per‑year market opportunity while dramatically reducing the environmental footprint of AI infrastructure.

• Work at the intersection of AI, energy, and compute to create 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.

As a Reinforcement Learning Engineer, you will architect the core intelligence for Hammerhead’s ORCA platform. Reporting to the Head of AI / Reinforcement Learning Engineering, you’ll design, train, and deploy 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 passionate about applying cutting‑edge RL research to complex, real‑world industrial systems.

You will develop models that control physical assets like cooling systems and power distribution units to unlock massive efficiency gains in AI workloads.

• 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.
• Build and train RL agents that can generalize to real‑world, physical systems.
• Lead the transition of RL models from research and simulation to live deployment within the ORCA platform, ensuring stability and performance on mission‑critical hardware.
• Analyze agent performance to continuously improve control strategies for tasks such as peak shaving, workload shifting, and thermal management.
• Partner with platform engineers to define APIs, data telemetry, and infrastructure needed to support and scale our RL agents across a global portfolio of data centers.

• Proven experience developing and implementing reinforcement learning algorithms, demonstrated through publications in top conferences (e.g., NeurIPS, ICML, ICLR), open‑source contributions, or shipped products.
• 3+ years of experience applying RL to real‑world problems, preferably in industrial automation, robotics, autonomous vehicles, energy systems, or other physical systems. Experience from a leading industrial or academic RL lab is highly desirable.
• Deep proficiency in Python and modern ML frameworks such as PyTorch, Jax, or Tensor Flow. Experience with simulation platforms and RL libraries (e.g., Ray RLlib, Isaac Gym) is a plus.
• MS or PhD in Computer Science, Robotics, Operations Research, or a related field with a focus on machine learning or control theory.
• Strong theoretical background and the ability to bridge RL theory with the constraints of physical, real‑world systems.

• Competitive salary, bonus, 401(k) plan, and equity in a rapidly growing startup.
• Comprehensive health, dental, and vision coverage.
• Opportunity to apply the latest AI technologies working with an experienced team.

Referrals increase your chances of interviewing at Hammerhead

AI, Inc. by 2x.

Visit our Careers page /careers to apply.