At a Glance
- Tasks: Integrate cutting-edge ML models into autonomous driving software and develop simulation tools.
- Company: Oxa, a leader in autonomous vehicle technology, based in Oxford.
- Benefits: Competitive salary, hybrid working, private healthcare, and 25 days annual leave.
- Other info: Inclusive culture that values diversity and encourages innovation.
- Why this job: Join a world-class team solving exciting challenges in AI and robotics.
- Qualifications: Experience in ML, Python, and simulation frameworks; strong problem-solving skills.
The predicted salary is between 63000 - 77000 £ per year.
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.
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Software Engineer (Planning & Evaluation) in Oxford employer: Oxa
Oxa is an exceptional employer, offering a dynamic work environment in Oxford where innovation meets collaboration. With a focus on employee growth, we provide opportunities for technical leadership and mentorship within our cutting-edge Remote Operations team, alongside competitive benefits such as flexible working arrangements, comprehensive healthcare, and a pet-friendly office. Join us to be part of a pioneering team that is shaping the future of autonomous vehicle technology while enjoying a supportive culture that values diversity and individual needs.
StudySmarter Expert Advice🤫
We think this is how you could land Software Engineer (Planning & Evaluation) in Oxford
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Oxa or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Oxa.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Oxa.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Oxa that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Software Engineer (Planning & Evaluation) in Oxford
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Oxa.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Oxa and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Oxa
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Oxa uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.