Staff Machine Learning Engineer, Data Curation & Dataset Strategy

🧠 Your day-to-day

• 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 every model we're building

• 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 set 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

🧩 What you’ll be working on

• Defining our dataset content strategy: which data and metadata we need, and why, so training teams can select the most valuable data as smoothly as possible

• Steering data selection by what our model engineers need right now. For example, if we're weak at unprotected right turns at traffic lights, those scenarios go straight to hot storage

• Delivering large, measurable storage-cost savings as ingestion scales across our internal fleet and partner and OEM data

• Evolving from practical heuristics to ML-driven filtering, and influencing what gets filtered at the vehicle and edge

• Working as a pair with our Corpus Implementation Engineer to turn strategy into production systems

🙌 You should apply if

• You have strong autonomous-vehicle or robotics experience, working with large-scale driving, sensor or comparable data

• You're a principal, hands-on ML engineer who has built models that score, select or filter data

• You've operated at petabyte scale and are comfortable with the engineering that comes with it

• You're strong in Python and Spark, with large-scale cloud data experience

• You have strong quantitative intuition and use it to make practical, measurable decisions

• You're pragmatic and high-ownership, and can set direction across several teams without direct authority

• You bring experience in data selection, retention or filtering for model training, edge or vehicle-side filtering, computer vision or high-volume IoT data, or leading small cross-functional groups (any of these is a bonus)

🌱 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.