ML Infrastructure Engineer, Fauna

Job description

We are seeking a Machine Learning Engineer to work directly alongside our research scientists to train, evaluate, and deploy the models that make our robots move, perceive, and act in the real world. This is a hands-on ML role: you will train policies, debug convergence, run experiments in simulation, and push models onto hardware — not just build the pipes around them.

You’ll bring deep expertise in reinforcement learning, computer vision, and supervised learning applied to robotics and embodied systems. You also need to think seriously about training infrastructure — managing GPU clusters, optimizing distributed training, and shipping models to edge devices — but the core of this role is…

Job requirements

5+ years of non-internship professional software development experience
5+ years of programming with at least one software programming language experience
5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
Experience as a mentor, tech lead or leading an engineering team
Bachelor's degree or above in robotics, mechanical/mechatronics engineering, systems engineering or related field
Knowledge of data structures, algorithm design, statistics, and system design
Experience leading the design, build and deployment of complex and performant (reliable and scalable) software solutions in production
Experience facilitating discussions with senior leadership regarding technical / architectural trade-offs, best practices, and risk mitigation

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ML Infrastructure Engineer, Fauna

Job description

Job requirements

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