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Data Labeler Remote Jobs in California (NOW HIRING)

Corvus Robotics

Sr. ML Ops Engineer

Mountain View, CA · On-site +1

$123K - $169K/yr

Build and maintain the data pipeline infrastructure that consolidates internal infra, labeling ... hybrid or remote role with periodic trips to HQ in Mountain View, CA. Must Haves * 2-3 years ...

Faraday Future

Embodied AI Tooling Engineer

El Segundo, CA · On-site +1

$100K - $120K/yr

Teleoperation & Remote Orchestration: Engineering low-latency tools for remote robot * control and ... Design sophisticated data "scrubbing" and labeling interfaces to * accelerate the creation of high ...

Faraday Future

Embodied AI Tooling Engineer

El Segundo, CA · On-site +1

$100K - $120K/yr

Teleoperation & Remote Orchestration: Engineering low-latency tools for remote robot * control and ... Design sophisticated data "scrubbing" and labeling interfaces to * accelerate the creation of high ...

Workila

Full Stack Engineer

San Francisco, CA · On-site +1

Strong background with data structures and algorithms (CS/Mathematics deg) NICE-TO-HAVES * 1+ year ... Remote work not available TRAVEL Travel not required VISA Candidate visas are not supported ...

UMT - Internal

VP, Engineering

San Francisco, CA · On-site +1

$212K - $273K/yr

... Data Science to deliver intuitive, artist-first experiences that drive growth, retention, and label partner success. This role is based in SanFrancisco with four days in-office and one day remote.

UMT LLC

Staff Product Manager

San Francisco, CA · On-site +1

... Data Science to deliver intuitive, artist-first experiences that drive growth, retention, and label partner success. This role is based in San Francisco with four days in-office and one day remote.

UMT - Internal

Staff Product Manager

San Francisco, CA · On-site +1

... Data Science to deliver intuitive, artist-first experiences that drive growth, retention, and label partner success. This role is based in SanFrancisco with four days in-office and one day remote.

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Data Labeler Remote information

What does a remote data labeler do?

A remote data labeler is responsible for annotating or tagging data—such as images, videos, audio, or text—from a remote location, typically working from home. Their work helps train machine learning models by providing accurate, labeled datasets that algorithms use to learn and make predictions. Data labelers follow specific guidelines to ensure consistency and accuracy, and may use specialized software tools to complete their tasks. This role is essential in industries like artificial intelligence, self-driving cars, and natural language processing. Remote data labelers often work as freelancers or as part of distributed teams for tech companies.

What are the key skills and qualifications needed to thrive as a remote data labeler?

To thrive as a Data Labeler Remote, you need strong attention to detail, basic data analysis skills, and familiarity with data annotation processes, often supported by a high school diploma or equivalent. Proficiency with labeling platforms, annotation tools, and sometimes knowledge of spreadsheet software are typically required. Reliability, time management, and effective communication are crucial soft skills for maintaining accuracy and meeting project deadlines in a remote setting. These skills ensure high-quality, consistent labeled data, which is essential for training reliable machine learning models.

What are some common challenges faced by remote data labelers and how can they be managed?

Remote data labelers often encounter challenges such as maintaining focus during repetitive tasks, ensuring consistent annotation quality, and communicating effectively with distributed teams. To manage these, it's helpful to establish a structured work routine, take regular breaks to prevent fatigue, and use annotation guidelines provided by employers. Leveraging collaboration tools for feedback and clarification also helps maintain high-quality output and fosters a sense of connection with team members.

What is the difference between Data Labeler Remote vs Data Annotator Remote?

AspectData Labeler RemoteData Annotator Remote
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageCommon in AI/ML data preparationCommon in AI/ML data preparation
Job FocusLabeling data points for machine learningAnnotating data for training AI models

Both Data Labeler Remote and Data Annotator Remote roles involve preparing data for AI and machine learning projects. While the terms are often used interchangeably, Data Labeler Remote typically emphasizes labeling data points, whereas Data Annotator Remote may include more detailed annotation tasks. Both roles require similar skills and are performed remotely, making them accessible for individuals seeking flexible data-related jobs.

How much does a data labeler remote make?

Remote data labelers typically earn between $12 and $20 per hour, depending on experience, complexity of tasks, and the company. Some positions may offer additional incentives or flexible schedules, but wages generally align with entry-level data annotation roles in the industry.

Is data labeling a good career?

Data labeling is a common entry-level role in the AI and machine learning industry, involving annotating data such as images, text, or audio to train algorithms. It often offers flexible remote work options and requires attention to detail but typically has lower barriers to entry and limited career advancement without additional skills or certifications.

What are the most commonly searched types of Data Labeler jobs in California?

The most popular types of Data Labeler jobs in California are:

What are popular job titles related to Data Labeler Remote jobs in California?

For Data Labeler Remote jobs in California, the most frequently searched job titles are:

What job categories do people searching Data Labeler Remote jobs in California look for?

The top searched job categories for Data Labeler Remote jobs in California are:

What cities in California are hiring for Data Labeler Remote jobs?

Cities in California with the most Data Labeler Remote job openings:

Data Labeler Remote jobs near you
Infographic showing various Data Labeler Remote job openings in California as of September 2026, with employment types broken down into 88% Full Time, 6% Part Time, and 6% Contract. Highlights an 100% Remote job distribution.

Sr. ML Ops Engineer

Mountain View, CA • On-site, Remote

Corvus Robotics
Trucking • 11 - 50 employees
Learn more about Corvus Roboticsexternal

$123K - $169K/yr

Full-time

Re-posted 3 days ago

Job description

About Corvus
Every physical good spends time in a warehouse, and every warehouse tracks their inventory. Today, nearly 100% of warehouses track their inventory manually using barcode scanners and climbing forklifts.
We're Corvus Robotics. Our fully autonomous Corvus One™ drones use computer vision & robotics to automatically track inventory, improving worker safety and increasing labor efficiency. We believe that data-driven, safe inventory management will optimize the global physical economy and improve economic prosperity for humanity.
About the Role
With a growing fleet of autonomous drones and an expanding customer base, we're now ready to multiply ML iteration speed and unblock more advanced ML product delivery.
We're hiring a systems-oriented Senior Software Engineer to build the data infrastructure, training pipelines, and internal tooling that our ML team needs to move faster.
Specifically in this role you will:
  • Build and maintain the data pipeline infrastructure that consolidates internal infra, labeling tools, S3, and other data sources into a unified, queryable system
  • Build tooling for dataset selection and curation that can programmatically target specific data (by environment, object type, etc.)
  • Own ML data infra from robot to training run, accessible to the ML team without backend engineering help
  • Build model evaluation and regression testing infrastructure -- real metrics, not vibes or "someone complained in prod"
  • Automate the model retuning loop for standard tasks so ML engineers can be mostly hands-off on routine updates

This is a hybrid or remote role with periodic trips to HQ in Mountain View, CA.
Must Haves
  • 2-3 years shipping real production ML infrastructure for big datasets, not just scripts
  • Experience building distributed data pipelines that consolidate multiple sources
  • Demonstrated understanding of data flow from raw collection, labeled training set, to trained models
  • Experience building systems from scratch, or contributed heavily to a small-team infra build where the playbook didn't exist
  • Ability to thrive in a startup environment with high ambiguity. You'll figure out what to build

Nice to Haves
  • Experience setting up annotation tooling and workflows
  • Background in robotics autonomy and computer vision

Experience integrating with tools like Kubeflow, SLURM, or similar for scalable training workflows

Apply