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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
In this role, you will develop vision-language-action models for our onboard Behavior & Planning stack, with the goal of improving safe and robust decision-making in complex, long-tail driving scenarios. You will work on multimodal models that connect scene understanding, contextual reasoning, and planning-relevant representations for real-world autonomous driving.
This role is focused on advancing state-of-the-art VLAs for autonomy, including model development, large-scale training, fine-tuning, evaluation, and onboard optimization. You will work closely with partners across behavior, planning, perception, systems, and infrastructure to translate research advances into practical capabilities deployed on our vehicles.
If you are excited about building and deploying cutting-edge VLA systems for real-world robotics, we'd love to hear from you.
About the Work
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Develop and advance VLA models for onboard Behavior & Planning in autonomous driving systems.
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Build multimodal models that improve safe decision-making in complex, ambiguous, and long-tail driving scenarios.
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Research and apply state-of-the-art approaches in vision-language-action modeling, multimodal representation learning, and foundation models for autonomy.
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Train, fine-tune, and evaluate large-scale VLAs using diverse real-world driving data.
Improve model quality, robustness, and generalization across challenging edge cases and dynamic real-world environments. -
Optimize models for onboard deployment, including inference efficiency, latency, memory usage, and runtime performance.
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Collaborate with autonomy, data, and infrastructure teams to define training, evaluation, and deployment requirements.
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Design effective evaluation methodologies for multimodal models in safety-critical applications.
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Contribute to scalable model and data pipelines that support rapid experimentation and production deployment.
About You
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You have deep expertise and prior experience in some or many of the following areas:
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You have an M.S. or Ph.D. in Computer Science, Machine Learning, Robotics, Artificial Intelligence, or a closely related field.
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You have 5+ years of industry and/or research experience in machine learning, with a focus on large-scale model development.
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You have strong experience with vision-language models (VLMs), multimodal foundation models, VLAs, or related architectures.
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You have hands-on experience with large-scale model training, fine-tuning, and evaluation.
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You have familiarity with core model components and techniques relevant to modern multimodal systems, such as Vision Transformers (Vi Ts) and large language models (LLMs).
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You have experience optimizing models for deployment, including inference speed, memory efficiency, and performance under onboard compute constraints.
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You have strong programming skills in Python and experience with modern deep learning frameworks such as Py Torch, JAX, and/or Tensor Flow.
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You are an independent researcher and strong collaborator who can move fluidly from early-stage ideas to practical implementation.
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You thrive in a fast-paced research and development environment and are excited to deploy advanced ML systems in the real world.
Nice to Have
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Experience applying VLMs/VLAs or other foundation models to autonomous driving, robotics, or embodied AI.
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Familiarity with behavior, planning, scene understanding, or decision-making systems in AVs.
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Experience with multimodal data curation, dataset development, or data quality systems at scale.
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Experience with onboard ML deployment in real-time or resource-constrained environments.
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Publications in top-tier machine learning, robotics, or computer vision conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, CoRL, RSS, or ICRA.
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Strong C++ skills or experience integrating ML models into production systems.
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.
At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected pay range is between $183,825.00 and $275,975.00/year 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.
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1
応募クリック数
0
模擬応募者数
0
スクラップ
0
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Nuroについて

Nuro
Series BFocused 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
ニュース&話題
Uber and Lucid’s Robotaxis Just Hit the Streets. Here’s When You Can Ride Them - inc.com
inc.com
News
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6d ago
Uber and Nuro begin employee testing of a Lucid Gravity robotaxi in San Francisco - The Next Web
The Next Web
News
·
1w ago
Uber and Nuro start robotaxi test rides in posh Lucid EVs - How-To Geek
How-To Geek
News
·
1w ago
Uber and Nuro begin testing premium robotaxi service in San Francisco
·
1w ago
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