MLOps Engineer for AI Accelerator Hardware

Lumai Limited; Oxford; On-site; GBP 90,000 - 140,000; Full time

Benefits offered by this job

Share Option Scheme

Pension Scheme

Private Health Insurance

Cycle to Work

L&D Allowance

Subsidised On-site Lunches

25 days holidays

Job summary

Lumai Limited is building a breakthrough AI accelerator for data centers using 3D optical compute. We seek a senior MLOps Engineer to own end-to-end ML pipelines, tooling, and production deployments for models from research to silicon-validated production.

In this high-ownership role, you’ll collaborate with ML researchers, compiler engineers, and hardware architects to optimize model-to-chip workflows, instrument deployments, and maintain CI/CD for ML across on-prem and cloud environments.

Qualifications

• 5+ years of software or infrastructure engineering experience, with at least 2 years in an ML or AI-adjacent role
• Strong Python skills and familiarity with major ML frameworks (PyTorch or JAX)
• Hands-on experience building and operating ML pipelines in production
• Experience with experiment tracking and model lifecycle management tools (MLflow, W&B, DVC, or similar)
• Solid understanding of containerisation (Docker) and orchestration (Kubernetes or Slurm) for distributed compute workloads
• Infrastructure-as-code mindset: Terraform, Ansible, or equivalent; CI/CD pipelines (GitHub Actions, Jenkins, or similar)
• Experience with hardware-accelerated compute (CUDA/GPU workflows)
• Strong debugging and observability skills: distributed tracing, logging, metrics dashboards
• Ability to work effectively in a fast-moving, ambiguous environment where the hardware and software are both being built simultaneously
• Strong preference for: custom accelerator hardware, ML compiler stacks, model optimisation techniques, on-chip profiling, and open-source contributions
• Experience in a deeptech, semiconductor, or hardware startup environment

Responsibilities

• Design and operate end-to-end ML pipelines: data ingest, training, evaluation, quantisation, and deployment onto custom AI accelerator hardware
• Build and maintain experiment tracking, model registry, and versioning infrastructure
• Own CI/CD for ML: automated testing of model correctness, numerical accuracy, and on-chip performance
• Develop and maintain tooling for benchmarking model inference on custom silicon, including latency, throughput, power, and utilisation metrics
• Collaborate with ML researchers, compiler engineers, and hardware architects to remove bottlenecks across the model-to-chip workflow
• Instrument and monitor production inference deployments; design alerting and rollback strategies
• Manage compute resource scheduling across on-premises accelerator clusters and cloud
• Drive infrastructure-as-code practices: containerisation, orchestration (Kubernetes/Slurm), and reproducible environment management
• Contribute to the internal developer platform: self-service tooling, documentation, and runbooks

Skills

Python

ML frameworks

ML pipelines

CI/CD

Docker

Kubernetes

Terraform/Ansible

CUDA/GPU

Observability

distributed compute

Tools

MLflow

Weights & Biases

Job description

Lumai Limited is building a breakthrough AI accelerator for data centers using 3D optical compute. We seek a senior MLOps Engineer to own end-to-end ML pipelines, tooling, and production deployments for models from research to silicon-validated production.

In this high-ownership role, you’ll collaborate with ML researchers, compiler engineers, and hardware architects to optimize model-to-chip workflows, instrument deployments, and maintain CI/CD for ML across on-prem and cloud environments.