Staff Machine Learning Engineer - Ops

Highlights

• Own the release process for driving models that power real autonomous vehicles.
• Protect the model baseline while making model delivery faster and more reliable.
• Build evaluation and monitoring that improve confidence in production releases.

What they offer

• Salaries benchmarked against the market annually
• Meaningful equity sharing in long-term success
• Relocation support and visa sponsorship where applicable
• Hybrid working with core hours and hands-on work in workshops and labs
• Learning and development budgets for training and conferences
• Comprehensive benefits including health, dental, parental leave, pension, wellbeing support and team socials

Ideal candidate

You are a quality-obsessed integrator who thrives on ambiguous, cross-team problems and fixing root-cause process issues. You balance rigour with speed to ship safe autonomy reliably.

Requirements

• Significant software integration and release experience including branching strategies, release cadences and configuration management
• Understanding of ML training, model lifecycles and infrastructure required to deliver models reliably
• Ability to review model, architecture or code changes and challenge decisions misaligned with intent
• Experience with ML tooling such as PyTorch, TensorRT, model registries, quantisation or model deployment
• Comfortable working with CI/CD systems and GitHub Actions
• Ownership of ambiguous, cross-team problems with focus on fixing underlying processes
• Strong quality mindset with judgement on when speed matters
• Clear communication and collaboration across research, engineering, platform, evaluation and product teams