Staff Machine Learning Engineer, Data Curation & Dataset Strategy

Wayve • Sunnyvale, CA

2d • $390,000 - $460,000 • Hybrid

About The Position

Wayve’s datasets team owns the driving data its AI Driver learns from, including ingestion, annotation, retrieval and data quality. As the company’s data grows from hundreds of petabytes towards exabyte scale, the role will shape decisions about what data to retain and where to store it, influencing model quality and storage costs across the company.

The role will develop and own an ingestion-time model to score incoming driving data and route it to hot, cold, archive or delete storage. It will work with model training teams to define useful data distributions, deliver initial cost savings through practical heuristics, and develop ML-driven filtering. The role will also help establish company-wide data policy and lead hands-on work with a small group of software and ML engineers to build data provisioning and provenance features into Corpus.

Wayve builds an end-to-end AI platform for autonomous driving, with a mapless and hardware-agnostic approach intended to support vehicles across a range of automation levels. The company works in a hybrid model, combining office collaboration with remote work.

Requirements

• Strong autonomous-vehicle or robotics experience working with large-scale driving, sensor or comparable data.
• Experience as a hands-on ML engineer building models that score, select or filter data.
• Experience operating at petabyte scale and familiarity with the associated engineering challenges.
• Strong Python and Spark skills, with large-scale cloud data experience.
• Strong quantitative intuition and the ability to make practical, measurable decisions.
• A pragmatic, high-ownership approach and the ability to set direction across several teams without direct authority.

Nice To Haves

• Experience in data selection, retention or filtering for model training.
• Experience with edge or vehicle-side filtering.
• Computer vision experience.
• Experience with high-volume IoT data.
• Experience leading small cross-functional groups.

Responsibilities

• Build and own the ingestion-time model that scores incoming driving data and routes it to hot, cold, archive or delete.
• Work with training teams to define the right data distributions for each model being built.
• Deliver early storage-cost savings through practical heuristics, then develop ML-driven filtering.
• Partner with ingestion, annotation, retrieval, data quality, model training, AV/robotics, evaluation and storage teams to establish company-wide data policy.
• Lead and work hands-on with a small group of software and ML engineers to build data provisioning and data provenance features into Corpus.
• Define dataset content strategy, including which data and metadata are needed and why.
• Steer data selection according to model engineers’ current needs, prioritizing valuable scenarios for hot storage.
• Deliver measurable storage-cost savings as ingestion scales across internal fleet, partner and OEM data.
• Influence what data is filtered at the vehicle and edge.
• Work with the Corpus Implementation Engineer to turn strategy into production systems.

Benefits

• Market-benchmarked salaries, reviewed annually.
• Meaningful equity.
• Relocation support and visa sponsorship where applicable.
• Hybrid working and core hours.
• Opportunity to work hands-on in vehicle workshops and labs.
• Learning and development budgets, with support for training, conferences and growth.
• Comprehensive benefits including health insurance, dental insurance, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships and team socials.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed