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Data Labeling Autonomous Jobs (NOW HIRING)

Hirevouch

Applied Research Engineer

San Francisco, CA · On-site

Frontier Data Labeling Service : Specialized data labeling through Aligner, leveraging subject ... You'll know exactly what you're responsible for and have the autonomy to execute. We empower people ...

Amazon

Machine Learning Data Linguist, Alexa AI

Seattle, WA · On-site

$130K - $156K/yr

... autonomously with minimum direction - Building a thorough understanding of conventions and ... Label, generate, and ensure the quality of datasets. - Work closely with ML Data Linguists and ...

Avala AI, Inc

3D Computer Vision Engineer

San Francisco, CA · On-site

$130K - $190K/yr

We specialize in high-quality data labeling, dataset management, and data visualization-offering 4D labeling solutions for autonomous vehicles, humanoid robots, and drone applications. Our mission is ...

HappyRobot Inc

Data Operations Lead

San Francisco, CA · On-site

$150K - $200K/yr

... autonomously across voice, email, and enterprise systems. Born in Y Combinator (S23) and backed by ... Lead Labeling Teams: Direct both in-house and third-party labeling teams by setting guidelines ...

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Data Labeling Autonomous information

What are the key skills and qualifications needed to thrive as a Data Labeling Autonomous Specialist, and why are they important?

To thrive as a Data Labeling Autonomous Specialist, you need attention to detail, a strong understanding of data annotation protocols, and familiarity with data labeling best practices, often supported by relevant technical or analytical experience. Proficiency in data labeling tools such as Labelbox, Supervisely, or CVAT, and sometimes experience with Python or other scripting languages, is typically required. Strong organizational skills, focus, and the ability to work independently make someone stand out in this position. These skills and qualities are important because accurate data labeling directly impacts the quality of machine learning models and overall project success.

What is the difference between Data Labeling Autonomous vs Data Labeling Specialist?

AspectData Labeling AutonomousData Labeling Specialist
CredentialsTypically no formal certifications required; familiarity with labeling tools beneficialOften requires basic training or certifications in data annotation
Work EnvironmentPrimarily remote, independent work with automation toolsCan be remote or on-site, often supervised or team-based
Industry UsageUsed in AI/ML projects for autonomous data processingCommon in data annotation firms and tech companies

Data Labeling Autonomous focuses on automated or semi-automated labeling processes, requiring minimal manual intervention, while Data Labeling Specialist involves manual annotation tasks with more direct human input. Both roles are essential in AI development but differ in automation level and work setup.

What are common challenges faced by Data Labeling Autonomous professionals, and how can they be addressed?

Data Labeling Autonomous professionals often encounter challenges such as handling ambiguous or edge-case data, maintaining consistency across large datasets, and meeting tight deadlines while ensuring high-quality annotations. These challenges can be addressed by adhering to clear labeling guidelines, participating in regular team calibration sessions, and using annotation tools that support quality checks. Collaboration with machine learning engineers and project managers also helps clarify requirements and resolve uncertainties, contributing to more accurate and useful labeled data.

What is data labeling in the context of autonomous systems?

Data labeling for autonomous systems involves assigning meaningful tags or labels to raw data—such as images, video, or sensor readings—so that machine learning models can recognize and interpret different objects, actions, or scenarios. This process is crucial for training autonomous vehicles or robots to accurately detect pedestrians, road signs, obstacles, and other relevant elements in their environment. High-quality data labeling ensures that autonomous systems can make safe and reliable decisions in real-world situations.
Infographic showing various Data Labeling Autonomous job openings in the United States as of May 2026, with employment types broken down into 75% Full Time, and 25% Part Time. Highlights an 50% In-person, and 50% Remote job distribution.

Senior / Staff Machine Learning Engineer - Perception Attributes

Zoox

Foster City, CA • On-site

$242K - $333K/yr

Full-time

Medical, Life, PTO

Posted 6 days ago

Job description

As a machine learning engineer within the Attributes team in the Perception department, you will take ownership of developing and enhancing sophisticated behavioral models for various road users, including vehicles, pedestrians, and cyclists. Your work will focus on creating and maintaining robust perception attribute models that generate critical signals for our autonomous driving stack. These signals are essential inputs that enable our Prediction and Planning teams to make intelligent, safe driving decisions for our autonomous vehicles.
The Attributes team is fundamental to Zoox's autonomous driving capabilities. The models you develop will serve as the foundation for how our vehicles understand and interact with other road users, directly contributing to the safety and effectiveness of our autonomous driving system. By creating reliable and accurate behavioral models, you enable Zoox's vehicles to make smart, safe decisions in complex urban environments, bringing us closer to our goal of revolutionizing urban mobility.
In this role, you will...
  • Lead the development of sophisticated behavioral models for vehicles, pedestrians, and cyclists as a key member of the Attributes team within Zoox's Perception department.
  • Create and maintain perception attribute models that generate essential signals, enabling our autonomous vehicles to understand and predict the behavior of various road users.
    • >
  • You will collaborate closely with Prediction and Planning teams to optimize your models' outputs, directly influencing how our autonomous vehicles make real-time driving decisions.
    • >
  • Work with data labeling and ontology teams on data labeling and ontology definitions of the road users in different attributes and generate auto-labeling or data mining strategies for different attributes.
    • >
  • You will help shape the future of autonomous mobility by bridging the critical gap between raw perception data and autonomous decision-making.
    • >

Qualifications:
  • MS/PhD in computer science or related fields with a minimum of 7 years of relevant experience
    • >
  • Experience with training and deploying Deep Learning models
    • >
  • Experience with knowledge distillations from large foundation models
    • >
  • Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
    • >
  • Fluency programming in Python and extensive experience with algorithm design
    • >
  • Strong mathematics skills
    • >

Bonus Qualifications
  • Familiarity of VLMs/VLAs/ViTs
    • >
  • Experience with large model distillation in a production environment
    • >
  • Familiarity with C++
    • >

$242,000 - $333,000 a year
Base Salary Range
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
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Accommodations
If you need an accommodation to participate in the application or interview process please reach out to [email protected] or your assigned recruiter.
A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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