Staff ML Release Engineer - Ops & CI/CD

Wayve; Greater London; Hybrid; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Hybrid working

Relocation support

Equity / stock options

Health insurance

Learning & development budget

Job summary

Wayve is seeking to strengthen its Model Integration and Release Team. The role focuses on releasing driving models with robust quality gates, monitoring, and CI/CD workflows to ensure safe, reliable production deployments.

You’ll collaborate across ML engineering, evaluation, AI Platform, and product teams. You will review model changes, assess evaluation outcomes, and drive improvements in release processes, balancing speed with rigorous validation to maintain a high baseline.

Qualifications

• Significant software integration and release experience across ML models, architectures and data changes.
• Ability to review model, architecture, or code changes and ensure alignment with stated intent.
• Experience with ML tooling and technologies and CI/CD systems to deliver reliable production releases.

Responsibilities

• Define and evolve model development and release processes, including branching strategies, release cadence, configuration management, and quality gates.
• Review proposed model, architecture, code, and metric changes to ensure outcomes match intent.
• Assess evaluation results and determine whether releases meet quality and safety standards.
• Identify delivery bottlenecks and work across teams to address root causes.
• Balance speed and rigour, deciding when to accelerate or validate further.

Skills

Release processes

ML training

CI/CD

GitHub Actions

PyTorch

TensorRT

Model registries

Quantisation

Code review

Tools

PyTorch

TensorRT

GitHub Actions

Model registries

CI/CD tooling

Job description

Wayve is seeking to strengthen its Model Integration and Release Team. The role focuses on releasing driving models with robust quality gates, monitoring, and CI/CD workflows to ensure safe, reliable production deployments.

You’ll collaborate across ML engineering, evaluation, AI Platform, and product teams. You will review model changes, assess evaluation outcomes, and drive improvements in release processes, balancing speed with rigorous validation to maintain a high baseline.