
Machine Learning Engineer, Application Software
About this role
Based in Sunnyvale, California, the Machine Learning Engineer, Application Software role at Wayve involves designing and delivering ML-driven autonomous driving features, and it suits an experienced professional with a track record in shipping deep learning systems to production. Wayve builds embodied intelligence for real vehicles and autonomous driving ecosystems.
Role Overview
This full-time position is based in Sunnyvale, California, or Detroit, Michigan, operating on a hybrid working model. The Machine Learning Engineer drives critical initiatives to design and deliver machine learning behaviors scaling from assisted to autonomous driving. The role spans model architecture, data pipelines, evaluation frameworks, and real-world deployment while collaborating closely with AI Platform, Simulation, Robot Software, and Model Release teams.
Key Responsibilities
Requirements
Nice to Have
Skills and Tools
Salary and Benefits
About the Company
Wayve builds the leading AI platform for autonomous driving, pioneering an end-to-end AI approach that allows vehicles to learn directly from real-world experience. The mapless and hardware-agnostic AI platform integrates with global OEM partners, enabling continuous software evolution from L2 plus to L4 automation.
How to Apply
Candidates should apply on the official company careers page.
Skills and tech stack
Questions candidates ask
What is the salary and equity offering for this role?
The salary ranges from $311,850 to $350,625 and includes offers of equity.
Where is the job located?
The role is based in Sunnyvale, California or Detroit, Michigan, utilizing a hybrid working model.
What programming languages and frameworks are required?
Proficiency in Python is required, along with experience in C++ or CUDA, and confidence using PyTorch.
Is visa sponsorship available?
Yes, relocation support and visa sponsorship are provided where applicable.
What does the interview process consist of?
The process includes an initial 30-minute recruiter screen, 2 hours of competency interviews covering Python programming and PyTorch debugging, a 1-hour deep-dive technical interview on system design and ML, and a 45-minute final interview focused on mission and values alignment.