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Video Labelling Jobs in California (NOW HIRING)

Mercor

Software Engineer, Robotics Data

San Francisco, CA · On-site

$130K - $500K/yr

... video, depth, inertial, audio, and more) and turn it into validated, privacy-safe, delivery-ready datasets for frontier labs. Ingest, segmentation, pre-labeling, automated QC, and packaging, at ...

Figure

Data Quality Analyst

San Jose, CA · On-site

Responsibilities : • Use proprietary annotation tools to label objects, poses, and interactions in images and video streams from our humanoid robots • Collaborate with ML engineers to refine ...

Figure

Data Quality Analyst

San Jose, CA · On-site

Responsibilities : • Use proprietary annotation tools to label objects, poses, and interactions in images and video streams from our humanoid robots • Collaborate with ML engineers to refine ...

Create Music Group

Project Manager

Los Angeles, CA · On-site

$70K - $80K/yr

The company operates as a record label, distribution company, and entertainment network which ... Commission video and photo content such as: music videos (i.e. director selection, treatment and ...

Zensors

AI/ML Infrastructure Engineer

San Francisco, CA · On-site

$126K - $166K/yr

... per video stream to enable massive scalability of our SaaS product. * Data Management: Building, improving, maintaining, and operating systems to facilitate the collection, labeling, and use of ...

Adobe

Sr. Research Engineer

San Francisco, CA

$123K - $169K/yr

... labeling at scale. Required skills * Pipeline-building experience at scale for audio and/or video data with reproducibility and versioning * Deep audio domain knowledge: common datasets, quality ...

Umusic

Account Lead

Beverly Hills, CA

Partner with label digital teams to ensure campaigns are innovative and platform-native, with a strong emphasis on video strategy, fan engagement, and discovery through YouTube and emerging formats ...

Universal Music Group

Account Lead

Beverly Hills, CA · On-site

Partner with label digital teams to ensure campaigns are innovative and platform-native, with a strong emphasis on video strategy, fan engagement, and discovery through YouTube and emerging formats ...

Adobe, Inc.

Sr. Research Engineer

San Francisco, CA · On-site

$123K - $169K/yr

... labeling at scale. Required skills * Pipeline-building experience at scale for audio and/or video data with reproducibility and versioning * Deep audio domain knowledge: common datasets, quality ...

Adobe

Sr. Research Engineer

San Jose, CA

$122K - $168K/yr

... labeling at scale. Required skills * Pipeline-building experience at scale for audio and/or video data with reproducibility and versioning * Deep audio domain knowledge: common datasets, quality ...

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Video Labelling information

What does a video labelling do?

A typical day in Video Labelling involves reviewing video footage, identifying and annotating specific objects or events according to project guidelines, and entering this data into specialized software tools. Team members often collaborate with data scientists, engineers, or quality assurance leads to ensure accuracy and consistency in the annotations. Depending on the project and employer, you may work independently or as part of a larger team, sometimes with set quotas or deadlines. This work is crucial for developing and refining AI and machine learning models, making attention to detail and adherence to standards especially important. Over time, experienced video labelling professionals may progress to quality assurance roles or team leads overseeing larger annotation projects.

What are the key skills and qualifications needed to thrive in video labelling, and why are they important?

To thrive as a Video Labelling professional, you should have excellent attention to detail, basic computer proficiency, and familiarity with visual content analysis. Knowledge of annotation platforms, video editing software, or AI training tools is often required, and experience with data labelling systems can be beneficial. Strong communication, reliability, and the ability to follow detailed guidelines are important soft skills for this role. These abilities ensure high-quality, consistent data annotation that directly supports machine learning and computer vision projects.

What is a video labelling?

A Video Labelling job involves annotating or tagging objects, actions, or events in video footage to train machine learning models. This process helps AI systems recognize and interpret visual data accurately. Tasks may include drawing bounding boxes, classifying scenes, or adding timestamps for specific events. Video labelling is commonly used in industries like autonomous driving, security surveillance, and content moderation.

What are the most commonly searched types of Video Labelling jobs in California? The most popular types of Video Labelling jobs in California are:
What are popular job titles related to Video Labelling jobs in California? For Video Labelling jobs in California, the most frequently searched job titles are:
What job categories do people searching Video Labelling jobs in California look for? The top searched job categories for Video Labelling jobs in California are:
What cities in California are hiring for Video Labelling jobs? Cities in California with the most Video Labelling job openings:
Video Labelling jobs near you
Infographic showing various Video Labelling job openings in California as of July 2026, with employment types broken down into 81% Full Time, 15% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Software Engineer, Robotics Data

Mercor

San Francisco, CA • On-site

$130K - $500K/yr

Full-time

Medical, Dental, Vision

Posted 8 days ago

Job description

About Mercor
Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents.
Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You'll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.
About the Role
Frontier AI is going physical, and the labs building it are bottlenecked on one thing: high-quality data from the real world. Mercor pairs its operational scale with the specialized engineering that physical-world data demands.
You'll build the data backbone of physical AI: the pipelines that take raw multi-sensor capture from the field (video, depth, inertial, audio, and more) and turn it into validated, privacy-safe, delivery-ready datasets for frontier labs. Ingest, segmentation, pre-labeling, automated QC, and packaging, at petabyte scale across thousands of concurrent collectors.
What You'll Do
  • Build the end-to-end sensor data pipeline: ingest from capture devices in the field, through segmentation, pre-labeling, QC, and packaged delivery to customers
  • Design automated QC that validates recordings at scale: timing and sync integrity, calibration health, sensor continuity, coverage against requirements
  • Establish dataset schemas, versioning, provenance, and versioning, so every delivery has a clear system traceability
  • Build shared processing components such as privacy redaction, transcription, encoding, format packaging across all offerings
  • Integrate VLM-assisted pre-labeling and quality scoring into production workflows without sacrificing debuggability or human oversight
What Makes This Role Different
  • High ownership, early. This is a young, strategically central product area; the product you build will shape Mercor's physical-world data collection standards
  • The data is the deliverable. The end product at Mercor is the data; what your pipeline produces is what shapes the models that large frontier lab trains on
  • Real physical-world scale. Your inputs come from devices operated by humans in global real world settings, for thousands of hours. Building systems that scale is precedent.
What We're Looking For
  • Strong production backend/data engineering experience - you've built and owned high-volume data pipelines
  • Experience processing video or sensor data at scale: large binary formats, streaming ingestion, distributed batch processing, object storage economics
  • Fluency in Python and comfortable with AWS
  • Genuine data taste: you can look at a sensor trace or a timing histogram and tell when something is off
  • Comfort in ambiguous, fast-moving problem spaces where requirements evolve with the customer
Nice to Have
  • Experience with robotics data formats and tooling (MCAP, ROS bags, protobuf, Foxglove), camera geometry, or multi-sensor calibration and synchronization
  • Computer vision or multimodal ML experience (detection, tracking, VLM-based labeling or QC)
  • Prior work on data engines for AV, robotics, or egocentric video
Benefits
  • Bi-annual performance bonus structure
  • Generous equity grant vested over 4 years
  • Up to $15k Relocation bonus
  • $10K housing bonus (if you live within 0.5 miles of our office)
  • $1.5K monthly stipend for meals
  • Free Equinox membership
  • $200 monthly laundry reimbursement
  • $200 monthly personal wellness reimbursement
  • Health, Dental, Vision insurance

Apply