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- Tasks: Design and optimise software for Machine Learning training in a dynamic team environment.
- Company: Join Rivian, a trailblazer in emissions-free Electric Adventure Vehicles, committed to adventure and sustainability.
- Benefits: Enjoy flexible work options, a collaborative culture, and the chance to make a real impact.
- Why this job: Be part of a mission-driven team that values innovation and outdoor exploration.
- Qualifications: Requires a degree in Computer Science and 6+ years of relevant experience in software engineering.
- Other info: Rivian is an equal opportunity employer, ensuring accessibility for all applicants.
The predicted salary is between 43200 - 72000 £ per year.
About Us
Rivian is 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
In this role, you will be responsible for the design, implementation, and optimization of software components related to our Machine Learning training. This position requires a passion for clean code and strong software development principles. The scope includes everything from how we architect, configure, and run our ML configuration systems to the training pipelines, testing pipelines, and general tooling that support our model development. You will collaborate closely with our team of ML engineers to seamlessly integrate your software components into our broader model development process.
Qualifications
- B.S., M.S. or Ph.D. in Computer Science, or a related field
- 6+ years related industry or research experience
- Strong software engineering fundamentals and language experience in C++ and Python
- Broad understanding of modern Perception systems and their architectures
- Experience in several of the following areas:
- Software for real-time safety-critical systems
- Software engineering for robotics or perception applications
- Machine learning model training, machine learning infrastructure, and associated tools
- Writing performant, real-time software
- Parallel Programming and working with hardware accelerators
- Cloud computing and large-scale data processing
Staff Software Engineer, Perception, Autonomy employer: Rivian Automotive
Contact Detail:
Rivian Automotive Recruiting Team
atcandidateaccommodations@rivian.com
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Software Engineer, Perception, Autonomy
✨Tip Number 1
Familiarise yourself with Rivian's mission and values. Understanding their commitment to sustainability and adventure will help you align your passion for clean code and software development with their goals, making you a more appealing candidate.
✨Tip Number 2
Showcase your experience in machine learning and perception systems during networking opportunities. Engage with professionals in the field through platforms like LinkedIn or relevant tech meetups to discuss your projects and gain insights into Rivian's work culture.
✨Tip Number 3
Prepare to discuss specific examples of your work with real-time safety-critical systems or robotics applications. Rivian values practical experience, so being able to articulate your contributions and the impact of your work will set you apart.
✨Tip Number 4
Demonstrate your ability to work in fast-paced environments by sharing experiences where you've successfully adapted to change or tackled challenges. This will highlight your readiness to thrive in Rivian's dynamic development setting.
We think you need these skills to ace Staff Software Engineer, Perception, Autonomy
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in software engineering, particularly with C++ and Python. Emphasise any relevant projects or roles that showcase your skills in machine learning, perception systems, and real-time software development.
Craft a Compelling Cover Letter: In your cover letter, express your passion for clean code and software development principles. Discuss how your background aligns with Rivian's mission and values, and mention specific experiences that demonstrate your ability to work in fast-paced environments.
Showcase Relevant Projects: Include a section in your application that details specific projects you've worked on related to machine learning, robotics, or perception applications. Highlight your role, the technologies used, and the impact of your contributions.
Prepare for Technical Questions: Anticipate technical questions related to software architecture, machine learning infrastructure, and parallel programming. Be ready to discuss your problem-solving approach and provide examples from your past work that illustrate your expertise.
How to prepare for a job interview at Rivian Automotive
✨Show Your Passion for Clean Code
As a Staff Software Engineer, you'll need to demonstrate your commitment to clean code and strong software development principles. Be prepared to discuss your coding practices and how you ensure maintainability and performance in your projects.
✨Highlight Relevant Experience
With 6+ years of experience required, make sure to highlight your background in software engineering, particularly in C++ and Python. Discuss specific projects where you've worked on machine learning training or perception systems to showcase your expertise.
✨Prepare for Technical Questions
Expect technical questions related to real-time safety-critical systems, robotics, and machine learning infrastructure. Brush up on these topics and be ready to solve problems on the spot, as this will demonstrate your ability to think critically under pressure.
✨Emphasise Team Collaboration
Rivian values teamwork, so be sure to share examples of how you've successfully collaborated with others in past roles. Discuss how you communicate effectively with team members, especially when integrating software components into broader projects.
