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Remote Data Labeling Jobs in California (NOW HIRING)

General Motors

Senior AI/ML Engineer

Sunnyvale, CA · On-site +1

$122K - $168K/yr

Remote/Hybrid:This role is based remotely but if you live within a 50-mile radius of Sunnyvale, CA ... The Data Labeling Engineering team designs, builds, and operates hybrid human/machine data labeling ...

General Motors

Senior AI/ML Engineer

Sunnyvale, CA · On-site +1

$124K - $170K/yr

Remote/Hybrid: This role is based remotely but if you live within a 50-mile radius of Sunnyvale, CA ... The Data Labeling Engineering team designs, builds, and operates hybrid human/machine data labeling ...

Mondo

Enforcement Operations Specialist

San Francisco, CA · On-site +1

$110 - $120/hr

Remote or Hybrid Start Date Is: ASAP Duration: 6 Months Contract (potential to extend) Compensation ... Strong data labeling, content review, or moderation experience * Ability to identify policy ...

HumanSignal

Strategic Projects Lead

San Francisco, CA · Remote

$75K - $110K/yr

... and remote workforce marketplaces can't. We own projects end-to-end, from scoping and protocol ... Our work spans RLHF, evals, red-teaming, and custom multimodal data creation, all powered by Label ...

HumanSignal

High Volume (TOFU) Recruiter

San Francisco, CA · On-site +1

$55K - $100K/yr

... standard for data labeling and evaluation, used by over 1 million practitioners worldwide. We ... San Francisco, CA preferred; open to other remote options About the Role HumanSignal Services runs ...

HumanSignal

Delivery Lead

San Francisco, CA · Remote

$110K - $140K/yr

... and remote workforce marketplaces can't. We own projects end-to-end, from scoping and protocol ... Our work spans RLHF, evals, red-teaming, and custom multimodal data creation, all powered by Label ...

Mercor

Chief Data Scientist

San Francisco, CA · Remote

$70 - $100/hr

Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams on ... Prior experience with data annotation , labeling, evaluation, or human feedback collection.

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How much do remote data labeling jobs pay per hour?

As of Jun 6, 2026, the average hourly pay for remote data labeling in California is $33.63, according to ZipRecruiter salary data. Most workers in this role earn between $16.71 and $45.43 per hour, depending on experience, location, and employer.

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

Remote data labelers often face challenges such as maintaining focus during repetitive tasks, managing volume-based workloads, and interpreting ambiguous data with consistency. To manage these, it's important to set up a distraction-free workspace, take regular breaks to avoid fatigue, and seek clarification from supervisors or project guidelines when uncertainties arise. Most companies provide onboarding and ongoing support to help new labelers understand annotation standards and best practices. Collaborating with remote team members via chat or project management platforms also helps maintain quality and stay connected. By being proactive and utilizing available resources, remote data labelers can maintain high accuracy and productivity.

What are the key skills and qualifications needed to thrive in the Remote Data Labeling position, and why are they important?

To thrive as a Remote Data Labeling specialist, you need strong attention to detail, basic data analysis skills, and the ability to accurately tag and categorize diverse data types, often with a high school diploma or equivalent. Familiarity with data labeling platforms, annotation tools (such as Labelbox or Amazon SageMaker Ground Truth), and, occasionally, basic knowledge of data privacy standards is helpful. Time management, self-discipline, and effective remote communication are valuable soft skills in this position. These skills ensure that labeled data is accurate and reliable, supporting the success of machine learning and AI projects.

What is a Remote Data Labeling job?

A Remote Data Labeling job involves annotating or categorizing data, such as images, text, audio, or video, to train machine learning models. Workers review and tag content based on specific guidelines provided by companies. This job is typically done online from home and requires attention to detail, consistency, and sometimes specialized domain knowledge. It plays a crucial role in improving artificial intelligence systems by providing high-quality labeled data.

What are the most commonly searched types of Data Labeling jobs in California? The most popular types of Data Labeling jobs in California are:
What are popular job titles related to Remote Data Labeling jobs in California? For Remote Data Labeling jobs in California, the most frequently searched job titles are:
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Remote Data Labeling jobs near you
Sr. Data Scientist, GenAI & Labeling Platforms

Sr. Data Scientist, GenAI & Labeling Platforms

Pinterest

San Francisco, CA • On-site, Remote

Other

Posted 19 days ago

Job description

Pinterest brings millions of people the inspiration to create a life they love. Advancements in Generative AI have opened up a wealth of opportunities for improvements in productivity and labeling quality, and we've only scratched the surface of its capabilities. Early results show strong promise for LLM-assisted labeling - reducing time and cost, focusing human rater efforts on higher-value problems, and improving the accuracy of our learnings.

This role focuses on advancing the science and systems behind labeling, evaluation, and GenAI-enabled workflows. The work spans LLM-assisted labeling, human-in-the-loop quality systems, prompt and rubric design, model evaluation, and methods for improving the speed, consistency, and usefulness of judgment-based data.

We're looking for a strong senior individual contributor to execute high-impact technical work in this space, partner cross-functionally to turn successful ideas into durable platform capabilities, and grow with the team as the space evolves.

What you'll do:

We are looking for an experienced and highly capable Data Scientist to help us drive step function improvements in our data labeling capabilities at Pinterest. In this role, you will:

  • Execute high-impact scientific work across GenAI-powered labeling and evaluation systems
  • Identify opportunities where LLMs and related methods can improve quality, speed, coverage, and cost efficiency
  • Develop prototypes that demonstrate value in areas such as prompt optimization, task decomposition, quality estimation, routing, and human-in-the-loop workflows
  • Design experiments and measurement frameworks to evaluate model performance, workflow outcomes, and operational tradeoffs
  • Partner with engineering, product, and data science teams to productionize successful approaches
  • Apply standards for trustworthiness, including bias measurement, calibration, quality control, and responsible oversight
  • Contribute to reusable methods and frameworks that can scale across teams and use cases
  • Support more junior scientists and contribute to the technical health of the team

What we're looking for:

  • 6+ years of combined post-graduate academic and industry experience (or PhD + 3 years) applying scientific methods to real-world problems on large-scale data
  • Strong hands-on experience as an individual contributor solving technically complex, high-impact data science or ML problems
  • Experience applying LLMs or other generative AI techniques to practical workflows, systems, or products
  • Ability to turn ambiguous problems into rigorous analyses, experiments, and prototypes
  • Track record of writing high-quality code and using technical work to influence product or platform direction
  • Solid cross-functional collaboration skills and experience working effectively across teams
  • Business and product sense with the ability to define meaningful success metrics
  • Self-directed learning mindset and comfort working in a rapidly evolving technical landscape
  • Experience with labeling systems, evaluation frameworks, human judgment workflows, or internal AI tooling is strongly preferred

Relocation Statement:

  • We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.

In-Office Requirement Statement:

  • This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.

  • This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

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