Machine Learning Engineer, ADAS at Wayve
May no longer be active — verify on the employer site
At a glance
- Company
- Wayve
- Location
- United Kingdom
- Work arrangement
- On-site
- Employment type
- Full-time
- Experience
- 2–5 years
- Working hours
- 40 hours
- Visa sponsorship
- Offered, according to the listing
- Posted
- Added to The Stack
✨ The Stack take on this Wayve job
- 🏢 Wayve has 44 jobs here, 42 with visa sponsorship see all
- 🛂 Skilled Worker visa. Standard minimum salary: £41,700 a year guide
- 💡 No salary shown. Ask Wayve if it is above the minimum.
Updated 2026-11-05, from our data and official sources.
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About the role
Responsibilities:
- Train, debug and improve computer vision and 3D perception models (detection, classification, instance segmentation).
- Own the full ML lifecycle: data collection, training, evaluation and iterative improvement.
- Build scalable data pipelines including auto-labelling and pseudo-labelling to accelerate dataset generation.
- Develop offline systems (tracking, 3D reconstruction) to propagate high-quality labels through time.
- Optimize models for online/in-car constraints when required (latency, compute footprint).
- Collaborate with engineers and product teams to prioritize work based on measurable evaluation signals.
Requirements:
- Proven experience shipping CV-focused deep learning systems (applied ML engineering, not research-only).
- Familiarity with 3D perception concepts and pipelines (LiDAR, multi-view geometry, tracking, reconstruction).
- Strong software skills in Python and experience with PyTorch or TensorFlow; C++ is a plus.
- Experience building and evaluating large-scale datasets and labelling pipelines.
- Pragmatic problem-solver who can own projects end-to-end and iterate from metrics and failure cases.
- Effective communicator and collaborator within cross-functional teams.
Responsibilities
Develop and improve computer vision and 3D perception models for ADAS, focusing on detection, classification, and instance segmentation. Build scalable data pipelines and offline reconstruction tools to accelerate model training and evaluation.
Requirements
Candidates must have a proven track record of shipping CV-focused deep learning systems and experience with 3D perception concepts like LiDAR or multi-view geometry. Strong applied ML engineering skills and the ability to own the full ML lifecycle are required.
Key skills
- Computer Vision — in 30 other listings on The Stack
- 3D Perception — in 7 other listings on The Stack
- Deep Learning — in 50 other listings on The Stack
- Machine Learning Engineering — in 5 other listings on The Stack
- PyTorch — in 92 other listings on The Stack
- TensorFlow — in 55 other listings on The Stack
- LiDAR — in 7 other listings on The Stack
- Multi-view Geometry — in 6 other listings on The Stack
- Instance Segmentation
- Object Detection
- Data Pipeline Construction
- 3D Reconstruction
- Auto-labelling
- Pseudo-labelling
- System Design
- Programming
On The Stack (as of 2026-11-05)
Frequently asked questions about Wayve
Is this Machine Learning Engineer, ADAS role still open?
It was posted on 2026-07-07. Listings more than 30 days old may no longer be active, so check Wayve's site before applying.
Does Wayve offer visa sponsorship?
This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on Wayve's site.
Where is this role located?
The listing gives the location as United Kingdom. It is marked on-site.
What skills does this role ask for?
The listing names: Computer Vision, 3D Perception, Deep Learning, Machine Learning Engineering, PyTorch, TensorFlow, LiDAR, Multi-view Geometry, Instance Segmentation, Object Detection, Data Pipeline Construction, 3D Reconstruction, Auto-labelling, Pseudo-labelling, System Design, Programming.