At a Glance
- Tasks: Evolve core components of a cutting-edge simulation platform for driving intelligence.
- Company: Join Wayve, a leader in autonomous vehicle technology with a collaborative culture.
- Benefits: Enjoy a competitive salary, hybrid work options, and a focus on professional growth.
- Other info: Inclusive workplace with a commitment to diversity and equal opportunity.
- Why this job: Make a real impact in the future of driving technology while working with innovative teams.
- Qualifications: 5+ years in software development, excellent Python skills, and experience with Kubernetes.
The predicted salary is between 70000 - 90000 € per year.
The role involves working as a software engineer for Wayve’s Simulation Technology team, evolving core components of Wayve’s simulation platform used to develop and evaluate driving intelligence.
Responsibilities include:
- Shaping and implementing the technical roadmap in key areas: robot emulator fidelity, visual fidelity, or efficient scaling.
- Collaborating with robotics, research, platform, and data teams to ensure accurate, scalable simulations.
- Owning KPIs for simulator cost, SLOs, throughput, latency, etc.
- Aligning technical dependencies and guiding technical discussions across the company.
- Integrating components of the simulated robot, machine-learned graphics subsystems, and production-quality software (Python).
About you:
Essential skills:
- Experience with workflow orchestration systems (Airflow, Dagster, Flyte, etc.) and/or data-intensive applications.
- Excellent Python development skills.
- Deep knowledge of Kubernetes at the user level.
- Systems-oriented engineering design: reusable, extensible code.
- Understanding of software performance issues and design tradeoffs.
- 5+ years industry experience designing and programming software.
- Excellent communication and people engagement skills.
Desirable skills:
- Experience with autonomous vehicles or robotics.
- Proficiency in Go or C++.
- Experience scaling simulations or data-intensive workloads.
- Experience designing, implementing, and optimizing large-scale machine learning inference systems in cloud GPU environments.
- Experience operating/scaling modern machine-learned graphics techniques (NeRF, Gaussian Splatting, GenAI).
This is a full-time role based in our London office. We operate a hybrid working policy with both office and remote work options and core working hours.
Wayve is committed to creating an inclusive interview experience. If you require accommodations or adjustments to the interview process, please let us know. We value diversity, inclusion, and equal opportunity. All qualified candidates are encouraged to apply.
From a legal perspective, we comply with anti-discrimination laws and do not inquire about protected characteristics during the interview process.
Senior Software Engineer, Cloud, Simulation in London employer: Wayve
Wayve is an exceptional employer that fosters a collaborative and innovative work culture, particularly for those passionate about advancing simulation technology in the autonomous vehicle sector. With a commitment to employee growth, we offer opportunities for professional development and a hybrid working policy that promotes work-life balance. Our London office is a vibrant hub where diverse talents come together to shape the future of driving intelligence, making it a rewarding place to build your career.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Software Engineer, Cloud, Simulation in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Wayve. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you've got a GitHub or portfolio, make sure it's up to date. Share projects that highlight your Python prowess and experience with cloud technologies.
✨Tip Number 3
Prepare for the technical interview by brushing up on your knowledge of Kubernetes and workflow orchestration systems. We love seeing candidates who can talk shop and dive deep into tech discussions.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows us you're genuinely interested in joining the Wayve team.
We think you need these skills to ace Senior Software Engineer, Cloud, Simulation in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your Python development skills and any experience with workflow orchestration systems, as these are key for us.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about simulation technology and how your background aligns with our needs. Be sure to mention any relevant projects or experiences that showcase your expertise in cloud environments.
Showcase Your Communication Skills:Since excellent communication is essential for this role, make sure your application materials are clear and well-structured. We want to see how you engage with complex ideas and collaborate with teams.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Wayve
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills and get familiar with Kubernetes. Since the role involves shaping the technical roadmap, be ready to discuss your experience with workflow orchestration systems like Airflow or Dagster. Prepare examples of how you've tackled software performance issues in the past.
✨Showcase Your Collaboration Skills
This position requires collaboration with various teams, so think of specific instances where you've worked cross-functionally. Be prepared to share how you’ve aligned technical dependencies and guided discussions in previous roles. Communication is key, so practice articulating your thoughts clearly.
✨Demonstrate Your Problem-Solving Abilities
Expect questions that assess your systems-oriented engineering design skills. Prepare to discuss design trade-offs you've made in past projects, especially in relation to reusable and extensible code. Think about challenges you've faced in scaling simulations or data-intensive applications and how you overcame them.
✨Be Ready for Technical Questions
Given the focus on machine learning inference systems and modern graphics techniques, review relevant concepts and be ready to dive deep into technical discussions. You might be asked to solve a problem on the spot, so practice coding challenges in Python and brush up on your knowledge of autonomous vehicles or robotics.
