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Remote Data Labeling Jobs in California (NOW HIRING)

... 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 ...

... 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 ...

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 ...

Lead Data Analyst

Foster City, CA · Remote

$120K - $160K/yr

We run these virtual- and private-label marketplaces in one of the nation's largest media networks ... REMOTE QuinStreet is an equal opportunity employer. We do not discriminate on the basis of race ...

Director Master Data Management

Irvine, CA · On-site +1

$143K - $228K/yr

Remote Position Summary: The Director - MDM COE is responsible for establishing and leading the ... labeling). Leadership & Change Management: * Build and lead a cross-functional team of data ...

Senior Data Analyst

Foster City, CA · Remote

$80K - $130K/yr

We run these virtual- and private-label marketplaces in one of the nation's largest media networks ... REMOTE QuinStreet is an equal opportunity employer. We do not discriminate on the basis of race ...

Senior Manager, Data Security

San Francisco, CA · On-site +1

$134K - $185K/yr

This role is remote-friendly within North America. For those who prefer in-office or hybrid work ... labeling approaches * Experience designing and operating DLP controls across endpoints, network ...

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Remote Data Labeling information

See California salary details

$10

$33

$75

How much do remote data labeling jobs pay per hour?

As of Aug 13, 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 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 skills and qualifications are needed for remote data labeling?

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 remote data labeling?

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:

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

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

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

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

Infographic showing various Remote Data Labeling job openings in California as of August 2026, with employment types broken down into 100% Part Time. Highlights an 100% Remote job distribution, with an average salary of $69,956 per year, or $33.6 per hour.

Senior Technical Program Manager, Human-in-the-Loop Operations

Roblox

San Mateo, CA • On-site, Remote

Full-time

Posted 5 days ago


Job description

As Senior Technical Program Manager for the Human-in-the-Loop (HITL) Operations, you will own the end-to-end lifecycle of Roblox's AI data labeling and model evaluation ecosystem. This is a high-leverage, high-ownership role at the intersection of Research, Engineering, and Operations. You will scale our data operations that is handling million of items evaluated annually today with projection of 4x the current volume by 2030, managing a multi-million annual budget and a distributed workforce of 100+ remote contractors - all while driving the platform evolution from manual workflows to AI-assisted, LLM-accelerated operations.

This is a rare opportunity to build the data infrastructure that directly determines the quality of Roblox's AI models across creator tools, content discovery, in-experience AI, and 3D generative content - at the exact moment when human judgment is the critical ingredient for getting these models right.

You Will

  • Lead data programs end-to-end. Own the full lifecycle of labeling and model evaluation workflows across Roblox's AI teams - from translating ambiguous ML requirements into structured annotation tasks, to overseeing contractor execution, quality review, and dataset delivery to model teams.
  • Define and maintain ground truth. Develop and iterate on labeling guidelines, annotation schemas, and quality frameworks tailored to Roblox's unique data types: 3D mesh quality, texture coherence, search relevance, game novelty detection, NPC behavior evaluation, and AI-generated Luau code assessment.
  • Manage a multi-vendor, distributed workforce. Oversee remote contractor teams, managing workforce allocation, productivity SLAs, quality calibration, and budget forecasting serving across multiple teams with Roblox.
  • Drive the shift to AI-assisted workflows. Partner with Engineering to evaluate and implement LLM-based pre-labeling, LLM-as-a-Judge evaluation, and automated QA routing - reducing FTE coordination overhead and scaling throughput proportional to our annual volume growth.
  • Partner cross-functionally across Roblox AI. Work closely with ML Engineers, Data Scientists, and Product Managers to translate model development needs into concrete, executable data programs, and communicate program status and quality trends to senior leadership.
  • Own operational excellence and KPIs. Define and track SLAs across throughput, inter-annotator agreement, cost per label, and data quality metrics. Surface risks, resolve bottlenecks, and drive continuous process improvement.
  • Shape platform and tooling strategy. Contribute to Roblox's next-generation labeling and evaluation platform strategy - including vendor pilots, internal platform improvements, and the transition to a hybrid human-AI collaborative workflow model.

You Have

  • 5+ years of experience in Technical Program Management, Data Operations, or Operations Management within an AI/ML or data-intensive environment.
  • Deep hands-on experience with data labeling, annotation, or model evaluation - including designing annotation schemas, writing labeling guidelines, and managing quality control at scale.
  • Proven experience managing external vendor relationships and distributed contractor workforces, including workforce planning, quality oversight, and budget management.
  • Strong understanding of the ML lifecycle and the role of human-labeled data in training, fine-tuning, and evaluating models.
  • Proficiency in SQL and Python for querying datasets, analyzing label quality, and building operational dashboards. At a minimum, be able to use AI tools to generate queries.
  • Excellent written and verbal communication skills - able to write rigorous technical specifications and present complex data concepts to both ML researchers and business stakeholders.
  • Proven ability to drive cross-functional alignment and exercise strong judgment, knowing when to champion collaborative efforts versus leading independently.
  • Exceptional critical thinking skills with a demonstrated capacity to navigate ambiguity and execute effectively in 0-to-1 environments without structured guidance.
  • Solid grasp of software development life cycles and hands-on experience leveraging AI-assisted tools like Cursor, Claude, or Gemini to accelerate workflows.

Nice to Have

  • Experience with LLM-based labeling pipelines, LLM-as-a-Judge evaluation, or human-AI calibration loops.
  • Familiarity with labeling platforms such as Label Studio, Scale AI, or Snorkel AI.
  • Experience evaluating 3D, games, videos, or multimodal data beyond standard text and image annotation.
  • Background in vendor platform evaluation or build vs. buy analysis.
  • Experience with data operations at a consumer platform operating at massive scale (100M+ users).
  • Knowledge of Roblox platform and its games, or general gaming experience.