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Data Annotation Jobs in Martinez, CA (NOW HIRING)

Sieve

Data Operations Lead

San Francisco, CA · On-site

... annotation, curation, and quality review • Build and improve QA processes to ensure data output meets the standards required by frontier AI labs • Own product ops for the data platform. Work with ...

Sesame

Technical Program Manager, Data

San Francisco, CA · On-site

$152K - $196K/yr

They are seeking a Senior Technical Program Manager to lead their data collection and annotation initiatives, ensuring the delivery of high-quality data while collaborating with research and product ...

Sesame

Technical Program Manager, Data

San Francisco, CA · On-site

$200K - $260K/yr

Lead audio data collection and annotation efforts at Sesame. * Collaborate with research and product teams to understand and formalize their requirements. * Identify and manage internal resources and ...

Specter

Data Operations Engineer

San Francisco, CA · On-site

$81K - $110K/yr

Build and maintain internal tooling for labelers, including annotation interfaces, task pipelines, and dataset browsers * Define and enforce quality control standards across all labeled data ...

Xdof

Technical Program Manager

San Francisco, CA · On-site

$152K - $196K/yr

Ensure data annotation projects meet client requirements on accuracy and SLA, while satisfying internal cost targets. * Collection & Annotation Solution Design: Develop a deep understanding of ...

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Data Annotation information

What does a data annotation do?

A typical workday as a Data Annotator involves reviewing datasets—such as images, audio, text, or video—and accurately labeling or categorizing information according to specific project guidelines. Most Data Annotators work independently, but they often collaborate with project managers or data scientists to clarify requirements and resolve ambiguities. Tasks may be repetitive, but adhering to precise standards is vital for maintaining data quality. Work environments can range from technology companies to remote or freelance settings, and advancement opportunities exist as team leads or quality assurance specialists for those who excel in consistency and reliability.

How much money can I make doing data annotation?

Data annotation jobs typically pay between $10 and $20 per hour, depending on the complexity of the task and the employer. Experienced annotators or those working on specialized projects may earn higher rates, especially if they have skills in specific tools or domains. Earnings can vary based on whether the work is freelance, part-time, or full-time, and some platforms offer bonuses for accuracy or speed.

What is a data annotation?

A Data Annotation job involves labeling and categorizing data, such as text, images, audio, or video, to help train machine learning models. Annotators apply tags, bounding boxes, or classifications to data based on specific guidelines. This process improves the accuracy of AI systems in recognizing patterns and making predictions. Many data annotation jobs require attention to detail and familiarity with specific domains. It is commonly used in applications like autonomous driving, natural language processing, and computer vision.

What are the key skills and qualifications needed to thrive in data annotation?

To thrive in Data Annotation, you need strong attention to detail, accuracy, and basic data handling skills, often supported by a high school diploma or equivalent. Familiarity with annotation platforms, data labeling software, or content management systems is frequently required, though specific certifications are rare. Excellent communication, time management, and the ability to focus on repetitive tasks distinguish top performers in this role. These skills are crucial because accurate and consistent data annotation directly impacts the quality of machine learning models and AI applications.

What are the most commonly searched types of Data Annotation jobs in Martinez, CA? The most popular types of Data Annotation jobs in Martinez, CA are:
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Data Annotation jobs near you
Infographic showing various Data Annotation job openings in Martinez, CA as of August 2026, with employment types broken down into 63% Full Time, 11% Part Time, and 26% Contract. Highlights an 72% In-person, 5% Hybrid, and 23% Remote job distribution.

Data Annotation Lead

Physical Intelligence

San Francisco, CA • On-site

Full-time

Re-posted 13 days ago

Job description

Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.
The role
We're looking for a Data Annotation Lead to own annotation operations and scale the team behind it. Annotation is core to how our models improve, and demand is growing fast. You will scale the annotation workforce from 100s to 1,000s while raising the quality bar - designing the org, the training pipeline, the quality system, and the metrics that let it scale efficiently.
You will own the people and the operation: throughput, quality, cost, and delivery across every annotation type.
In this role you will
  • Own annotation operations end-to-end: throughput, quality, cost, and on-time delivery across all annotation types.
  • Scale the annotation workforce from 100s to 1,000s: workforce planning, org design, and the hiring and onboarding funnel.
  • Build and lead a multi-layer management structure; hire, develop, and manage managers and team leads.
  • Scale throughput with autolabeling and model-based annotation: design human-in-the-loop workflows where models pre-label and annotators review, correct, and escalate, so output grows faster than headcount.
  • Stand up the training and certification pipeline that brings new annotators and teams to the quality bar quickly and consistently.
  • Define and continuously raise the quality bar: rubrics, calibration, audit/QA loops, and quality-adjusted productivity.
  • Establish operational metrics and reporting (presence, throughput, acceptance/rejection, rework) and drive week-over-week improvement.
  • Run capacity planning and prioritization against competing demand; allocate teams to the highest-impact work.
  • Manage performance at scale with clear standards, feedback, and a fair improvement/exit process.
  • Partner with product and engineering to define annotation tooling that unlocks throughput and quality.
  • Partner with research and project leads to translate annotation needs into clear instructions, rubrics, and SLAs.
  • Own the in-house vs. vendor mix and manage external partners where used.
  • Own the annotation operating budget and unit economics; improve cost-per-annotation while protecting quality.

What you'll bring
  • 7+ years leading scaled data or annotation operations, including teams in the 100s+.
  • 3+ years as a manager of managers.
  • Track record standing up 0→1 annotation programs.
  • Deep command of annotation best practices, operations, and strategy.
  • Experience integrating autolabeling and model-based annotation into human workflows; building human-in-the-loop pipelines that raise throughput without sacrificing quality.
  • Fluency with operational and quality metrics; data-driven management of large workforces.
  • Strong cross-functional partnership with product, engineering, and research/ML.
  • Clear written and verbal communication; able to set and hold standards across a large, distributed team.
  • Working understanding of ML and why annotation quality drives model performance.

Nice to have
  • Experience in robotics, autonomous vehicles, or frontier-AI data pipelines.
  • Experience managing distributed/global and/or vendor workforces.
  • Built annotation tooling or partnered tightly with a tooling team.
  • Experience training or fine-tuning autolabeling models, or partnering closely with the ML teams that do.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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