ML Infrastructure Engineer - Scale AI Training & Inference

Isomorphic Labs; City of Westminster; On-site; GBP 90,000 - 130,000; Full time

Job summary

Isomorphic Labs is seeking several software engineers to advance the ML infrastructure that powers scalable research and deployment of models. You will collaborate with engineering and research teams to evolve the platform for training and inference across large compute pools.

Ideal candidates bring strong Python skills, hands-on Kubernetes experience, and a track record in ML inference or research infrastructure, with comfort in multi-cloud environments and cloud platforms such as GCP.

Qualifications

• Strong Python programming experience.
• Hands-on Kubernetes experience.
• Experience with Google Cloud Platform (GCP).
• Experience with multi-cloud environments.
• Background in ML inference or training infrastructure.
• Proven ability to design and evolve large-scale systems.

Responsibilities

• Evolve the ML infrastructure platform to accelerate research at scale.
• Explore options to deploy agents to increase robustness of the platform.
• Develop the platform for distributed, performance-critical training and inference workloads.
• Partner with engineering, research and product teams to identify and deliver impact.
• Demonstrated ability to work independently in cross-functional teams.
• Build and evolve infrastructure or platforms at significant scale.
• Provide platforms to internal customers.
• Leverage Google Cloud Platform and multi-cloud environments.

Skills

Python

Kubernetes

GCP

Multi-cloud

ML inference infra

Distributed systems

Job description

Isomorphic Labs is seeking several software engineers to advance the ML infrastructure that powers scalable research and deployment of models. You will collaborate with engineering and research teams to evolve the platform for training and inference across large compute pools.

Ideal candidates bring strong Python skills, hands-on Kubernetes experience, and a track record in ML inference or research infrastructure, with comfort in multi-cloud environments and cloud platforms such as GCP.