At a Glance
- Tasks: Lead the design and experimentation of core pretraining datasets for embodied AI.
- Company: Wayve, a pioneering developer of Embodied AI technology.
- Benefits: Attractive salary, equity, flexible hours, and unique learning opportunities.
- Other info: Join a diverse team of world-class researchers and engineers.
- Why this job: Shape the future of autonomy and tackle significant challenges in AI.
- Qualifications: 3-5 years post-PhD experience in dataset design and multi-modal learning.
At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives. Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems. Our vision is to create autonomy that propels the world forward.
The role We’re looking for a senior Applied Scientist to lead the design and experimentation of Wayve’s core pretraining datasets for foundation models in embodied AI. This is a high-impact opportunity to shape the data that drives model generalization across cities, embodiments, and reasoning tasks. You'll work across research, data, and engineering teams to build world-class multi-modal datasets and define how we evaluate and improve them at scale.
Key responsibilities- Lead the design, curation, and analysis of large-scale pretraining datasets for embodied AI
- Develop and run data-centric experiments to optimize training effectiveness and generalization
- Collaborate with cross-functional teams in London, Sunnyvale, and Vancouver on data architecture and strategy
- Define and implement metrics and benchmarks to assess dataset quality and model-data interactions
- Contribute to research outputs, tools, and processes that elevate data as a core lever for progress
In order to set you up for success as a Senior Applied Scientist at Wayve, we’re looking for the following skills and experience.
Essential- 3–5 years of experience post-PhD, or equivalent experience in industry with a focus on dataset design, multi-modal learning, or pretraining
- Strong applied research track record, including publications in venues such as NeurIPS, ICML, ICLR, CoRL, CVPR, or similar
- Hands-on experience curating, filtering, and scaling large datasets (vision, video, or multi-modal) for machine learning models
- Proficiency with machine learning frameworks (e.g., PyTorch) and large-scale data processing (e.g., Ray, Spark, Flyte and other distributed compute infrastructure)
- Ability to design and run scientific experiments to evaluate dataset impact on model performance
- Strong communication and collaboration skills, with experience working across technical and cross-functional teams
- Experience with foundation model training pipelines and data selection for large-scale pretraining
- Familiarity with multi-modal, temporal, or sensor-rich datasets (e.g., video, LiDAR, text)
- Contributions to benchmark design, data-centric evaluations, or open-source tooling for dataset experimentation
- Attractive compensation with salary and equity
- Immersion in a team of world-class researchers, engineers and entrepreneurs
- A unique position to shape the future of autonomy and tackle the biggest challenge of our time
- Bespoke learning and development opportunities
- Relocation support with visa sponsorship
- Flexible working hours - we trust you to do your job well, at times that suit you and your time
- Benefits such as an onsite chef, workplace nursery scheme, private health insurance, therapy, daily yoga, onsite bar, large social budgets, unlimited leave
Remote Applied Scientist - WFM Data employer: Wayve
Wayve is an exceptional employer that champions a diverse and inclusive culture, fostering an environment where every employee's unique skills and perspectives are valued. With a commitment to innovation in Embodied AI technology, employees have the opportunity to work alongside world-class researchers and engineers, contributing to groundbreaking advancements in automated driving. The company offers attractive compensation, bespoke learning opportunities, and a flexible working environment, making it an ideal place for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Remote Applied Scientist - WFM Data
✨Tip Number 1
Network like a pro! Reach out to people 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! Prepare a portfolio or a project that highlights your experience with dataset design and multi-modal learning. This is your chance to shine and demonstrate what you can bring to the table.
✨Tip Number 3
Practice makes perfect! Get ready for interviews by doing mock sessions with friends or mentors. Focus on explaining your past projects and how they relate to the role at Wayve.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in being part of the Wayve team.
We think you need these skills to ace Remote Applied Scientist - WFM Data
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Applied Scientist role. Highlight your experience with dataset design and multi-modal learning, as these are key aspects of what we're looking for at Wayve.
Showcase Your Research:If you've got publications in top venues like NeurIPS or ICML, flaunt them! We love seeing a strong applied research track record, so make sure to include any relevant work that demonstrates your expertise.
Be Clear and Concise:When writing your application, keep it straightforward. Use clear language to explain your experience with machine learning frameworks and large-scale data processing. We appreciate clarity and directness!
Apply Through Our Website:Don't forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for this exciting opportunity at Wayve.
How to prepare for a job interview at Wayve
✨Know Your Stuff
Make sure you brush up on your knowledge of dataset design and multi-modal learning. Familiarise yourself with the latest research in the field, especially publications from NeurIPS or ICML. This will not only help you answer technical questions but also show your passion for the subject.
✨Showcase Your Experience
Prepare to discuss your hands-on experience with curating and scaling large datasets. Be ready to share specific examples of projects you've worked on, particularly those involving machine learning frameworks like PyTorch. This will demonstrate your practical skills and how they align with the role.
✨Collaboration is Key
Wayve values teamwork, so be prepared to talk about your experience working with cross-functional teams. Highlight instances where you collaborated with researchers, engineers, or other stakeholders to achieve a common goal. This will show that you can thrive in their inclusive environment.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about their current projects, challenges they face in dataset design, or how they measure success in their experiments. This shows your genuine interest in the role and helps you assess if Wayve is the right fit for you.
