Senior/staff Software Engineer, ML Data

Nuro Nuro · Robotics · CA · Autonomy

Nuro is seeking a Senior/Staff Software Engineer to lead their ML Data engine, focusing on transforming autonomy data into high-value training signals for AI models. The role involves designing and building scalable data pipelines, developing data products for researchers, creating tools for data introspection, integrating labeling operations, and operationalizing active learning methods. This is a technical leadership role at the intersection of autonomy, ML, and infrastructure.

What you'd actually do

  1. Design and build scalable data ingestion and processing pipelines that turn data streams into targeted training datasets.
  2. Work across autonomy teams and data infra teams to build effective ML data pipelines and products for ML engineers.
  3. Develop infrastructure and visualization tools that allow ML researchers to easily introspect data, identify model failure modes, query for new data samples, and understand data distribution shifts.
  4. Collaborate closely with the data operations team to define quality standards, automate quality control (QC), and streamline the feedback loop between model performance and annotation guidelines.
  5. Lead the engineering effort to operationalize research-grade active learning methods.

Skills

Required

  • 7+ years of experience with a proven track record of technical leadership architecting and delivering complex, multi-system ML data engineering data systems.
  • B.S./M.S. in Computer Science, Artificial Intelligence, Electrical Engineering, Robotics, or equivalent practical experience.
  • Understanding of end-to-end ML data pipelines and their interaction with model training and evaluation.
  • Strong proficiency in C++ and Python, with petabyte-level data management experience.
  • Experience taking data concepts (e.g., "uncertainty sampling") and turning them into stable, 24/7 production services.

Nice to have

  • Prior experience working in large companies with productionized AI systems working on data engines for large scale machine learning.
  • Experience in workflow orchestration, introspection UI/UX for data understanding, and ML frameworks for foundation model training.
  • Expertise in data-centric AI topics (active learning, pre-training) and their application in autonomous systems.
  • Subject matter expertise and research in one or more of the following areas: Machine Learning, Deep Learning, Robotics , and have some familiarity with the state of the art in ML for autonomous driving and data utilization.

What the JD emphasized

  • architecting and delivering complex, multi-system ML data engineering data systems
  • stable, 24/7 production services
  • data-centric AI topics

Other signals

  • ML Data engine
  • autonomy AI models
  • training signals
  • active learning
  • data mining