Senior/Staff Software Engineer, Behavior ML Data

Nuro; Mountain View (CA); On-site; USD 193,930 - 352,290; Full time

Benefits offered by this job

Annual performance bonus

Equity opportunities

Competitive benefits package

Job summary

A leading technology company in Mountain View is looking for a Senior/Staff Software Engineer to lead technical initiatives for their ML Data engine. The role involves designing scalable data systems to enhance autonomy AI models, collaborating across teams, and developing tools for ML researchers. Ideal candidates will have over 7 years of experience in ML data engineering, strong skills in C++ and Python, and a relevant degree. This position offers a competitive salary and benefits package.

Qualifications

• 7+ years of experience in complex ML data engineering.
• Understanding of ML data pipelines and model interaction.
• Proven track record of architecting multi-system solutions.

Responsibilities

• Design scalable data ingestion and processing pipelines.
• Work cross-functionally to build ML data products.
• Develop introspection tools for ML researchers.

Skills

Technical leadership

C++ proficiency

Python proficiency

End-to-end ML data pipelines

Data management

Education

B.S./M.S. in Computer Science or related field

Job description

Who We Are

Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world’s most scalable driver, combining cutting‑edge AI with automotive‑grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self‑driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale, empowering a safer, richer, and more connected future.

About The Role

We are looking for a Senior/Staff Software Engineer to serve as a technical leader for Nuro’s ML Data engine. You will sit at the critical intersection of Autonomy, Machine Learning, and Infrastructure, acting as an architect for the systems that feed our autonomy AI models.

As a member of the Autonomy team, you will execute the technical strategy for transforming massive amounts of autonomy data into high‑value training signals for autonomy decision making. You will design and build data products for autonomy researchers, develop queries for rare "needle‑in‑a‑haystack" scenarios, and trigger labeling and data ingestion workflows without human intervention. You will partner directly with Autonomy ML researchers to understand their data needs, collaborate with infrastructure teams to define the right data interfaces and APIs, and build robust data selection, simulation, and introspection tools that can process data at scale.

About The Work

• Data Pipeline Architecture: Design and build scalable data ingestion and processing pipelines that turn data streams into targeted training datasets. Lead initiatives to improve data quality, detect anomalies, and manage out‑of‑distribution examples to ensure robust model training and deployment.
• Cross‑Functional Leadership: Work across autonomy teams and data infra teams to build effective ML data pipelines and products for ML engineers.
• ML Tooling & Introspection: 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.
• Labeling Operations Integration: 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.
• Active Learning & Data Mining Engines: Lead the engineering effort to operationalize research‑grade active learning methods. Build systems that compute embeddings or run inference at scale, manage vector databases, and automatically sample the most informative data points for labeling.

About You

Required Qualifications

• 7+ years of experience with a proven track record of technical leadership architecting and delivering complex, multi‑system ML data engineering data systems.
• Education: 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.

Preferred Qualifications

• 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.
• You have subject matter expertise and research in one or more areas: Machine Learning, Deep Learning, Robotics, and some familiarity with the state of the art in ML for autonomous driving and data utilization.

Compensation & Benefits

Base pay is part of the total compensation package. For this position, the reasonably expected base pay range is between $193,930 and $352,290 for the level at which this job has been scoped. The base pay will depend on several factors, including experience, qualifications, education, location, and skills. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package.

EEO Statement

At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal‑opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics.