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, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.
About us
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. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. Join our world-class team as we tackle today's most complex challenges and pave the way for a smarter, safer future.
At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment. Make Wayve the experience that defines your career!
The role
- The Data Platform team owns the data, infrastructure and tooling for the data we use to develop a learned driver.
- You will be part of a growing group focussed on discovering the best data recipe for driving, exploring how far data can push autonomous driving performance.
- You will be working across functions with machine learning research engineers, virtual world simulation engineers, robotics engineers and safety drivers to ingest, enrich and visualise thousands of hours of driving data.
Examples Projects:
- Data governance tooling to control and audit access to data, as well as visualise what data is available and how it was created (data lineage).
- Quality control and validation of datasets e.g. removing examples of bad driving.
- Labelling, enrichment and augmentation of data at scale using thousands of GPUs simultaneously.
- Orchestration of data processing and machine learning workloads by building out infrastructure for running Flyte and notebook environments (e.g. Google collab) at scale.
About you
In order to set you up for success as a Technical Lead at Wayve, we’re looking for the following skills and experience.
Essential:
- 5+ years of professional experience in Software Engineering
- Proficiency in Spark and Kubernetes.
- Experience building reliable data pipelines to handle large data sets.
- Experience working with concurrent, parallel and distributed computing.
- Experience with cloud infrastructure (AWS, Azure and/or GCP).
- Knowledge of software engineering practices - what makes code reusable and extensible.
- Passion for infrastructure: building internal tooling and frameworks.
- Experience working closely with users, shaping data to fit their needs .
Desirable:
- Experience with Azure specifically, as this is our main cloud provider.
We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply.
This is a full-time role based in our office in Mountain View, California. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. We operate core working hours so you can determine the schedule that works best for you and your team.
For more information visit Careers at Wayve.
DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.
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