MLOps Engineer – AI Hardware Platform

Intellectual Capital Resources; Oxford; On-site; GBP 59,000 - 99,000; Full time

Benefits offered by this job

Equity

Benefits

Competitive package

Job summary

Intellectual Capital Resources is seeking an experienced ML engineer to own MLOps for next-generation AI hardware. The role focuses on building and maintaining production ML pipelines, model management, and deployment across cutting-edge accelerator hardware.

You will leverage Python, PyTorch or JAX, and CI/CD to automate testing, validation, and deployment while collaborating with ML, hardware, and compiler teams on performance optimisations and scalable infrastructure.

Qualifications

• MLOps experience building and maintaining production ML pipelines.
• ML infrastructure expertise including experiment tracking, model management, and deployment.
• Strong Python skills with experience using PyTorch, JAX, or similar frameworks.
• Platform engineering experience with Docker, Kubernetes, Slurm, and distributed systems.
• CI/CD knowledge for automating testing, validation, and deployments.
• Experience with performance optimisation, including profiling and benchmarking AI workloads.
• Infrastructure as Code experience with Terraform, Ansible, or similar tools.
• Monitoring and observability experience, including logging, metrics, and alerting systems.
• Collaborative mindset for working across ML, hardware, and compiler teams.
• Deep-tech experience, ideally within AI, semiconductors, or hardware startups.

Responsibilities

• Own MLOps for our pioneering AI hardware company.
• Work on breakthrough technology at the forefront of AI compute.
• Solve complex technical challenges on novel accelerator hardware.
• Influence product direction with high visibility and ownership.

Skills

MLOps

Python

PyTorch

JAX

CI/CD

Performance optimisation

Monitoring & observability

Deep-tech experience

Tools

Docker

Kubernetes

Slurm

Terraform

Ansible

Job description

Intellectual Capital Resources is seeking an experienced ML engineer to own MLOps for next-generation AI hardware. The role focuses on building and maintaining production ML pipelines, model management, and deployment across cutting-edge accelerator hardware.

You will leverage Python, PyTorch or JAX, and CI/CD to automate testing, validation, and deployment while collaborating with ML, hardware, and compiler teams on performance optimisations and scalable infrastructure.