AI / ML Systems Engineer

About the Client

We're working with an independent Artificial General Intelligence Lab that is pushing the limits of agentic AI, structured reasoning, and compact model architectures. They’re a small but well-funded team (around $5M ARR) operating right at the edge of what’s possible. Their focus isn’t on simply scaling bigger models, but on building systems that can reason, act, and persist over time.

They don’t care about degrees, titles or pedigree — what matters is capability. If you can reason deeply, move fast and push technical boundaries, you’ll thrive there.

The Role

They’re looking for an Infrastructure / Systems Engineer to own the core infrastructure, tooling, and distributed systems that power their research. This is not a maintenance role — you’ll be building the backbone of their cognition stack, enabling researchers to move faster and scale experiments more effectively.

You’ll work directly with the founder and senior scientists to design and implement the infrastructure that underpins their approach to agentic AI. The scope spans distributed training pipelines, high-performance compute orchestration, and building tools that streamline research workflows.


Key Responsibilities

• Design, build, and maintain distributed systems that support large-scale ML research
• Develop robust tooling to accelerate experimentation and model training
• Manage and optimise compute infrastructure (cloud and on-prem, as relevant)
• Partner with researchers to integrate infrastructure solutions into their workflows
• Proactively identify bottlenecks and create scalable solutions for long-term growth

• Strong background in distributed systems, cloud platforms, and infrastructure at scale
• Proficiency in Python and experience with ML/AI tooling (PyTorch, TensorFlow, JAX, or similar)
• Familiarity with containerisation, orchestration (Kubernetes, Docker), and CI/CD pipelines
• Experience supporting high-performance or research-oriented computing environments
• Ability to work in a fast-moving, exploratory setting with a high degree of ownership