Teams at MakerMaker.AI

Write and optimize GPU kernels for machine learning training and inference workloads. Profile hardware performance, improve memory and scheduling efficiency, integrate kernels into training and serving systems, benchmark end-to-end results, and maintain performance across evolving hardware and frameworks. Collaborate with research teams on algorithm-kernel co-design and share low-level performance expertise across the organization.

Research and develop autonomous multi-agent systems that plan, decompose tasks, choose experiments, evaluate outputs, and recover from failures. Design methods, coordination patterns, and evaluation frameworks for open-ended research workflows; run rigorous experiments, ship methods to production, and drive team research direction.

Build and own production-grade machine learning systems spanning data, training, evaluation, deployment, and observability. Translate research prototypes into reliable infrastructure, establish engineering standards, maintain experimentation pipelines, and partner closely with researchers. The role requires strong distributed systems experience, Python expertise, familiarity with PyTorch or JAX, and experience with tools such as Ray, Slurm, or Kubernetes.