Founding AI Infrastructure Engineer

Overview

In this role you will design and own the large-scale AI training infrastructure powering robotics-focused models. You will scale distributed training across GPUs and clouds, optimize throughput and costs, and turn vast simulation data into production-ready models. You’ll build tooling to accelerate research, collaborating closely with founders and the research team to tackle frontier challenges. This is a chance to shape the architecture and technical direction of a high-impact robotics AI startup from day one.

Pay / Benefits

• Meaningful equity
• Founding-team influence
• Collaborative, small team environment

Responsibilities

• Design and own large-scale AI training infrastructure
• Scale distributed model training across hundreds of GPUs and multiple cloud environments
• Optimize training throughput, GPU utilization and infrastructure costs
• Build systems translating simulation data into production-ready models
• Develop tooling and frameworks to accelerate research and experimentation
• Collaborate with founders and research team to resolve bottlenecks at the frontier of robotics
• Shape the architecture, culture and technical direction of the company from day one

Key requirements

• Large-scale distributed training experience
• PyTorch and modern deep learning frameworks
• Kubernetes, Slurm or GPU orchestration platforms
• AWS and specialist GPU cloud providers
• High-performance computing and distributed systems
• Training optimisation, memory management and networking
• MLOps tooling, CI/CD and experimentation frameworks
• Python and production-grade software engineering
• Computer vision, multimodal AI or transformer architectures

• Deeply technical and problem-solving mindset
• Thrives in small, ambitious teams
• Enjoys building from scratch and avoiding legacy systems
• Large-scale distributed training
• PyTorch and modern DL frameworks
• Kubernetes/Slurm or GPU orchestration

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