Staff Machine Learning Engineer – Ops

Overview

As Staff ML Engineer (Ops/Release) at Wayve, you will define and enforce release gates across the model training cycle, ensuring each phase is validated before advancing. You’ll drive excellence in ML delivery pipelines, fix bottlenecks, and align tooling with platform, CI/CD, and evaluation teams. Your work safeguards model baselines and enables reliable on-road performance, while shaping scalable, quality-focused ML operations. Join a high-trust, impact-driven team delivering on Wayve’s autonomy vision.

Responsibilities

• Collaborate with ML engineers, data engineers and product teams to deliver features end to end
• Review release content — model and metric changes, evaluation results — to ensure quality and safety before shipping
• Identify bottlenecks in the ML delivery pipeline and drive fixes that boost speed without sacrificing quality
• Collaborate with AI Platform teams to ensure tooling meets delivery needs, defining and building checks and automation
• Collaborate with CI/CD teams to adapt workflows and streamline model delivery
• Collaborate with evaluation teams to ensure evaluation methods are reliable, identify gaps, and drive new methodologies
• Stay up to date with the latest in MLOps practices and bring improvements into the workflow

Key requirements

• Full system thinker with experience introducing operational processes to build engineering excellence
• Strong ML Ops, model registry and ML lifecycle experience
• Deep technical depth in ML training
• Strong understanding of ML code infrastructure and best practices – experience with PyTorch, TensorRT, quantisation and model deployment
• Strong CI/CD and GitHub Actions experience
• Strong communications skills with a collaborative mindset

• Collaborative mindset
• Strong communication skills
• Problem-solving and analytical thinking
• ML Ops, model registry and ML lifecycle
• PyTorch
• TensorRT

…