Nuro
Software Engineer, ML Data Infrastructure
Mountain View, California (HQ)From $160.4kmidAdded 1 month ago
About this role
Nuro is seeking a Software Engineer focused on Machine Learning Data Infrastructure to enhance their autonomous driving technology. The role involves creating scalable data pipelines and ensuring high-quality training and evaluation data for autonomous systems.
What you'll do
- Design and develop large-scale data pipelines
- Create a storage system for diverse evaluation metrics
- Construct dashboards to present evaluation results
- Maintain systems for continuous testing and monitoring
- Develop data mining and annotation tools
- Scale data annotation labels using ML techniques
What they're looking for
- Proficiency in Python or similar languages
- Experience with large-scale data systems
- Technical standards and best practices knowledge
- Knowledge of GCP, GCS, or PostgreSQL
- Familiarity with data processing solutions
- Experience in system design and data workflow orchestration
- Knowledge of data engineering principles
Benefits
- Competitive salary ranging from $160,360 to $240,540
- Annual performance bonus
- Equity options
- Comprehensive benefits package
- Commitment to diversity and inclusion
- Support for psychological safety in the workplace
Opens the official application on the employer’s site. No login required.
Nuro
Nuro builds autonomous vehicle platforms and fleet operations systems, with a focus on reliability, safety, and over-the-air update infrastructure. The company is hiring reliability engineers, software engineers, and operations specialists to improve vehicle hardware resilience, enhance system automation, and ensure fleet operational excellence.
View all jobs at NuroLikely interview questions
- Can you walk us through a large-scale data pipeline you've designed or built? What challenges did you face with scale, and how did you ensure reliability and introspectability?
- Describe your experience with batch and streaming data processing. Which tools and frameworks have you used, and what trade-offs did you consider when choosing between them?