ML Planning Engineer — Autonomous Driving Systems (Hybrid)

Oxa; Oxford; Hybrid; GBP 90,000 - 120,000; Full time

Benefits offered by this job

Company share programme

Private healthcare

Pension and health plan

Gym discounts

Hybrid/remote-friendly

Job summary

Oxa, based in Oxford, UK, is hiring for a role integrating ML-based motion planning into the Oxa Driver stack. You will develop simulation and validation tooling, bridging offline training with on-vehicle performance within a hybrid/remote-friendly environment.

The position emphasizes Python and C/C++ software engineering, MTMOps practices, and close collaboration with multiple engineering teams to push autonomous driving capabilities forward.

Qualifications

• Understanding of how ML models interact with autonomous driving software stacks.
• Hands-on experience with simulation frameworks and closed-loop testing.
• Strong Python software engineering and system integration skills.
• Ability to design metrics that bridge simulation and real-world performance.
• Experience managing experiment cycles from simulation to model iteration.

Responsibilities

• Integrate ML-based motion planning models into the core planning and driving stack with real-time performance.
• Develop and maintain driving simulation and scenario generation tools for diverse edge cases.
• Design closed-loop evaluation frameworks to quantify system-level performance.

Skills

ML planning

Python

C/C++

Simulation tooling

Metrics design

Experiment management

GCP

MLOps

Tools

Driving simulators

Job description

Oxa, based in Oxford, UK, is hiring for a role integrating ML-based motion planning into the Oxa Driver stack. You will develop simulation and validation tooling, bridging offline training with on-vehicle performance within a hybrid/remote-friendly environment.

The position emphasizes Python and C/C++ software engineering, MTMOps practices, and close collaboration with multiple engineering teams to push autonomous driving capabilities forward.