Software Engineer (Planning & Evaluation)

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

Founded in 2014, Oxa is a global leader in autonomous vehicle (AV) technology, dedicated to accelerating Industrial Mobile Autonomy (IMA).

We develop advanced physical AI and robotics technology, anchored around our configurable and explainable self-driving software, Oxa Driver; development toolchain, Oxa Foundry; and fleet management software, Oxa Hub. We utilise hardware blueprints known as Reference Autonomy Designs (RADs) to enable the integration of sensors, compute and drive-by-wire systems into existing vehicles produced by OEMs.

Our solutions automate repetitive industrial driving tasks, such as the towing and carrying of goods in locations like ports, airports and manufacturing facilities, or asset and perimeter monitoring in environments such as solar farms or industrial plants. We’re helping global businesses to address critical challenges like labour shortages and rising operational costs - driving efficiency, productivity, and safety.

Based in Oxford, and with offices in Canada, our engineering team is drawn from the world’s top physical AI specialists and led by originators of the field.

Your Role:

You will join a growing team of computer science and robotics experts bridging the gap between cutting-edge machine learning and production autonomy. Your work will focus on integrating ML-based reasoning models into the broader Oxa Driver planning and driving stack, whilst developing the simulation and metrics tools necessary for closed-loop evaluation and validation at scale.

Key Responsibilities:

• Integrate state-of-the-art machine learning (ML) based motion planning models (e.g., Behaviour Cloning, Reinforcement Learning) into the core planning and driving software stack, ensuring seamless interoperability and real-time performance.
• Develop and maintain driving simulation and scenario generation tools to stress-test planning behaviors against diverse, safety-critical edge cases.
• Design and execute closed-loop evaluation frameworks that quantify system-level performance and provide rapid feedback for model improvement.
• Bridge the sim-to-real gap between offline model training, virtual testing, and on-vehicle performance by instrumenting, monitoring, and analyzing model behavior within the simulation environment.
• Collaborate across teams to ensure that ML planning models respect the constraints and requirements of the full autonomy stack, including perception, mapping, and vehicle control.
• You will be encouraged to share your ideas with the team and the wider business.
• You will interact with other teams to learn about the autonomy system and gain exposure to all aspects of the business.

What you need to succeed:

• Understanding of how ML models (particularly in motion planning) interact with broader autonomous driving software stacks.
• Hands-on experience with simulation frameworks, driving benchmarks, and closed-loop testing methodologies.
• Strong software engineering proficiency in Python with experience in system integration and building robust, maintainable tooling.
• Ability to design and interpret metrics that bridge the gap between simulation results and real-world safety/comfort performance.
• Experience in managing experiment cycles, from simulation to data-driven model iteration.
• Strong knowledge of trajectory tracking and optimization methods, used to score, evaluate, and refine trajectories generated by the ML Planner.
• An ability to understand both technical and commercial requirements.
• Familiarity with cloud platforms, preferably Google Cloud Platform (GCP)
• Experience with MLOps
• Experience working with driving simulators, autonomous driving software, or traffic modelling
• Familiarity with C or C++
• Competitive salary, benchmarked against the market and reviewed annually
• Company share programme
• Hybrid and/or flexible remote working arrangements
• Core benefits of market leading private healthcare, life assurance, critical illness cover, income protection, alongside a company paid health cash plan (including gym discounts)
• A salary exchange pension plan
• 25 days' annual leave plus bank holidays
• A pet-friendly office environment
• Safe assigned spaces for team members with individual and diverse needs

Our Culture:

We are on a mission to unlock the benefits of self-driving technology to every person and organisation on the planet. We are creating an environment where everyone, from any background, can do their best work which, put simply, is the right thing to do. We hire and nurture those we can learn from, valuing diversity and the innovation that this drives.

We promote an open and inclusive culture that empowers our Oxbots to bring their whole, authentic selves to work every day.

Why become an Oxbot?

Our team of experts in computer science, AI, robotics and machine learning is world-class, and together they’re solving the most exciting and important technological challenges of our times.

Our diverse, multi-cultural crew is guided by a shared vision to bring the myriad benefits of autonomy to our customers and partners. And in a company that celebrates uniqueness as much as skill and experience, we do it with energy, conviction and a healthy dose of excitement too.