Applied Scientist / Machine Learning Engineer

Wayve; United States; Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Hybrid working

Equity

Relocation support

Visa sponsorship

Vehicle labs access

Job summary

Wayve in Sunnyvale is seeking a data-centric ML engineer to help scale real-world driving data pipelines. You will work on data enrichment, labeling, and dataset curation for their end-to-end AI Driver and foundation models.

The role emphasizes production-ready research, Python-based tooling, and collaboration across foundation-model, evaluation, simulation, and infrastructure teams to push ideas into production.

Qualifications

• You have strong machine-learning and software-engineering fundamentals and can take applied research into production.
• Proficient in Python and a modern deep-learning framework and comfortable with SQL or large-scale data tools.
• Experience with data curation, foundation models, large-scale data wrangling, computer vision, or model evaluation.
• You can reason about sampling, class imbalance, label quality, dataset coverage, and experimental design.
• You enjoy ambiguous, cross-functional problems and communicate technical trade-offs clearly.
• Experience with autonomous driving, robotics, VLMs, active learning, similarity search, Spark, or distributed training is valuable.

Responsibilities

• Build scalable methods to discover rare, high-value, and safety-critical scenarios in fleet data.
• Use embeddings, active learning, similarity search, model-assisted mining, and smart sampling to improve dataset coverage.
• Design pipelines for automated enrichment, labelling, deduplication, and data-quality monitoring.
• Run experiments to understand which data mixtures and curation strategies improve model performance.
• Collaborate with foundation-model, evaluation, simulation, and infrastructure teams to move ideas into production.
• Build benchmarks and slice analyses that expose model blind spots and guide the next data and modelling iteration.

Job description

About our Engineering Teams

Wayve's engineering teams are building the AI, robotics, simulation, data, and systems foundations needed to deploy a generalisable AI Driver safely and at scale.

The Enrichment and Curation team transforms fleet-scale driving data into high-quality training datasets, enrichments, and evaluation benchmarks for Wayve's end-to-end AI Driver and foundation models.

Your day-to-day

• Build scalable methods to discover rare, high-value, and safety-critical scenarios in fleet data.
• Use embeddings, active learning, similarity search, model-assisted mining, and smart sampling to improve dataset coverage.
• Design pipelines for automated enrichment, labelling, deduplication, and data-quality monitoring.
• Run experiments to understand which data mixtures and curation strategies improve model performance.
• Collaborate with foundation-model, evaluation, simulation, and infrastructure teams to move ideas into production.
• Build benchmarks and slice analyses that expose model blind spots and guide the next data and modelling iteration.

What you'll be working on

• Petabyte-scale real-world driving and simulation datasets.
• Data engines and retrieval systems using Python, SQL, Spark, embeddings, and multimodal models.
• Training-data strategy for embodied vision-language and driving models.
• Automated enrichment, active learning, and model-assisted labelling.
• Evaluation datasets that connect data decisions to real-world driving outcomes.

You should apply if

• You have strong machine-learning and software-engineering fundamentals and can take applied research into production.
• You are proficient in Python and a modern deep-learning framework and comfortable with SQL or large-scale data tools.
• You have experience with data curation, foundation models, large-scale data wrangling, computer vision, or model evaluation.
• You can reason about sampling, class imbalance, label quality, dataset coverage, and experimental design.
• You enjoy ambiguous, cross-functional problems and communicate technical trade-offs clearly.
• Experience with autonomous driving, robotics, VLMs, active learning, similarity search, Spark, or distributed training is valuable.

Not ticking every box? That's totally okay! If you're passionate about autonomy and keen to learn, we encourage you to apply even if you don't meet every requirement.

More about Wayve

Wayve is building the leading AI platform for autonomous driving. We are pioneering an end-to-end AI approach that enables vehicles to learn directly from real-world experience, developing the ability to adapt, generalise and improve at scale.

Our ambition is to make autonomy universal. Wayve's mapless and hardware-agnostic AI platform integrates with global OEM partners, enabling continuous software evolution from L2+ through to L4.

How we work - Locations & Flexible Working

This role is based in Sunnyvale. We operate a hybrid working model combining in-person collaboration with focused time working remotely.

The Interview Process

1. Initial call / recruiter screen (25 min)
2. Competency interview (60 min)
3. Deep-dive interviews (Programming, System Design, ML Breadth, PyTorch Debugging; 3-4 hours)
4. Final interview focused on mission, values, and level alignment

What's in it for you (location dependent)

• Salaries benchmarked against the market annually
• Meaningful equity
• Relocation support and visa sponsorship where applicable
• Hybrid working and access to vehicle workshops and labs
• Learning and development support
• Comprehensive location-dependent health, family, retirement, and wellbeing benefits

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.

To learn more about what drives us, visit Val