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求人Nuro

Senior/Staff Software Engineer, ML Data

Nuro

Senior/Staff Software Engineer, ML Data

Nuro

Mountain View, California (HQ)

·

On-site

·

Full-time

·

1mo ago

必須スキル

Machine Learning

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.

In this role you will be a member of the Autonomy team responsible for executing 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. If you love solving challenging new problems with a mindset of deriving practical solutions to be used in the physical world, come join us

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. E.g. 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 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.

At Nuro, your base pay is one part of your 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. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package.

*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. *

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Nuroについて

Nuro

Nuro

Series B

Focused on licensing its proprietary Level 4 driving system, Nuro Driver, to automakers and mobility providers.

51-200

従業員数

Mountain View

本社所在地

$8.6B

企業価値

レビュー

3.8

10件のレビュー

ワークライフバランス

3.2

報酬

4.0

企業文化

4.1

キャリア

3.5

経営陣

3.4

65%

友人に勧める

良い点

Good team environment and colleagues

Flexible work arrangements

Competitive compensation and benefits

改善点

Work-life balance challenges and long hours

Management and communication issues

Limited career advancement opportunities

給与レンジ

68件のデータ

Mid/L4

Senior/L5

Mid/L4 · DATA SCIENTIST

1件のレポート

$234,000

年収総額

基本給

$180,880

ストック

-

ボーナス

-

$234,000

$234,000

面接体験

4件の面接

難易度

3.3

/ 5

期間

14-28週間

面接プロセス

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

よくある質問

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Past Experience