Step inside the world of self-driving freight, powered by the Aurora Driver. Delivering the benefits of self-driving technology safely, quickly, and broadly. Backed by Greylock, Index and Lightspeed.
About the role
Build and scale evaluation pipelines that compare model versions on large driving datasets: offline evals, slice-based metrics, regression detection, and model-vs-model reports. Own embedding and vector-search pipelines over driving data, versioned per model, so engineers can search, cluster and compare how any model represents the world. This is where you’d start: owning embedding generation and search end to end. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Typically 5+ years of professional software engineering experience building backend, data or ML infrastructure
- Strong Python, and proficiency with SQL
- Designed and operated large-scale batch or data pipelines on cloud infrastructure, including backfills, retries and cost management
- Built systems that measure or evaluate something: metrics, experimentation, evaluation or analytics platforms
- Experience with distributed compute and container orchestration (e.g. Kubernetes, AWS Batch or similar)
- ML evaluation infrastructure: eval harnesses, golden datasets, regression detection, A/B model comparison
More about this role
Aurora’s mission is to deliver the benefits of self-driving technology safely, quickly, and broadly.
The Aurora Driver will create a new era in mobility and logistics, one that will bring a safer, more efficient, and more accessible future to everyone.
At Aurora, you will tackle massively complex problems alongside other passionate, intelligent individuals, growing as an expert while expanding your knowledge. For the latest news from Aurora, visit aurora.tech or follow us on LinkedIn .
We’re searching for a Senior Software Engineer, ML Evaluation & Introspection Infrastructure to join our Behavior Analysis team, reporting to the team’s engineering manager. Aurora’s trucks already haul freight on Texas highways with no one on board, and every new version of the learned model that drives them has to prove, on real driving data, that it is better and safer than the one before. Behavior Analysis builds the systems that make that call: the evals that compare model versions, the embedding search that makes every driving scenario findable, and the introspection tools that show why a model did what it did. Engineers build more than 100 training and eval datasets a week through our tools....
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