At a Glance
- Tasks: Design and implement cutting-edge AI systems for autonomous driving.
- Company: Join Rivian, a leader in emissions-free electric vehicles.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Dynamic team environment focused on innovation and collaboration.
- Why this job: Make a real impact on the future of adventure and sustainability.
- Qualifications: Master’s or PhD in relevant fields with strong AI and robotics skills.
The predicted salary is between 60000 - 80000 £ per year.
About Us
Rivianis on a mission to keep the world adventurous forever.
This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract.
As a company, we constantly challenge what’s possible, never simply accepting what has always been done.
We reframe old problems, seek new solutions and operate comfortably in areas that are unknown.
Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.
Responsibilities
- Design and implementation of learning-based prediction and planning systems, including end-to-end models for real-world driving.
- Develop hybrid planning architectures that combine transformer-based prediction/planning with classical methods such as MPC and graph-based planning.
- Drive end-to-end ownership across data collection, dataset curation, model training, optimization, deployment, and closed-loop evaluation.
- Define and enforce safety and feasibility strategies for trajectory generation, including fallback behaviors and runtime safeguards.
- Partner with Perception and Systems teams to integrate planning models into production-like stacks and ensure robust interface contracts.
- Improve real-time inference performance for in-vehicle deployment using model optimization techniques and toolchains such as Tensor RT.
- Build and scale evaluation pipelines that connect offline metrics with closed-loop behavior in simulation and on-road testing.
- Lead scenario-based validation for rare and safety-critical edge cases, and use results to drive model and system improvements.
- Mentor peers and contribute technical leadership across planning and prediction initiatives.
Qualifications
- Master’s or Ph D in Robotics, Control Engineering, Computer Science, Electrical Engineering, Mechanical Engineering, or a related field.
- Strong background in autonomous driving prediction and planning, with hands‑on experience in both research and deployment.
- Deep knowledge of trajectory prediction and planning methods, including transformer-based architectures and sequence modeling.
- Strong fundamentals in control and robotics, including MPC, graph search, state estimation, and vehicle behavior modeling.
- Proficiency in Python and C++ for production-quality software development.
- Hands‑on experience with Py Torch and deployment acceleration frameworks (for example Tensor RT/ONNX) in real-time systems.
- Experience with ROS/Autoware-style robotics integration and simulation‑based development workflows.
- Strong understanding of open‑loop vs closed‑loop evaluation, KPI design, failure analysis, and safety‑driven model validation.
- Demonstrated technical leadership, cross‑functional collaboration, and ability to deliver under tight product timelines.
- Excellent communication and problem‑solving skills in fast‑paced, multidisciplinary environments.
- Company Statements
- Equal Opportunity
Rivian is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws.
All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender, gender expression, gender identity, genetic information or characteristics, physical or mental disability, marital/domestic partner status, age, military/veteran status, medical condition or any other characteristic protected by law.
Rivian is committed to ensuring that our hiring process is accessible for persons with disabilities.
If you have a disability or limitation, such as those covered by the Americans with Disabilities Act, that requires accommodations to assist you in the search and application process, please email us
Candidate Data Privacy
Rivian may collect, use and disclose your personal information or personal data (within the meaning of the applicable data protection laws) when you apply for employment and/or participate in our recruitment processes (“Candidate Personal Data”).
This data includes contact, demographic, communications, educational, professional, employment, social media/website, network/device, recruiting system usage/interaction, security and preference information.
Rivian may use your Candidate Personal Data for the purposes of (i) tracking interactions with our recruiting system; (ii) carrying out, analyzing and improving our application and recruitment process, including assessing you and your application and conducting employment, background and reference checks; (iii) establishing an employment relationship or entering into an employment contract with you; (iv) complying with our legal, regulatory and corporate governance obligations; (v) record‑keeping; (vi) ensuring network and information security and preventing fraud; and (vii) as otherwise required or permitted by applicable law.
Rivian may share your Candidate Personal Data with (i) internal personnel who have a need to know such information in order to perform their duties, including individuals on our People Team, Finance, Legal, and the team(s) with the position(s) for which you are applying; (ii) Rivian affiliates; and (iii) Rivian’s service providers, including providers of background checks, staffing services, and cloud services.
Rivian may transfer or store internationally your Candidate Personal Data, including to or in the United States, Canada, the United Kingdom, and the European Union and in the cloud, and this data may be subject to the laws and accessible to the courts, law enforcement and national security authorities of such jurisdictions.
Please note that we are currently not accepting applications from third party application services.
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StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning / AI Engineer in London
✨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 Rivian 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 Rivian.
✨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 Rivian.
✨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 Rivian 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 Senior Machine Learning / AI Engineer in London
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 Rivian.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Rivian 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 Rivian
✨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 Rivian 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.