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Annotation Jobs in Mountain View, CA (NOW HIRING)

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Annotation information

See Mountain View, CA salary details

$53.1K

$68.9K

$115K

How much do annotation jobs pay per year?

As of Sep 8, 2026, the average yearly pay for annotation in Mountain View, CA is $68,911.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,400.00 and $68,400.00 per year, depending on experience, location, and employer.

What is an annotation?

An annotation job involves labeling or tagging data, such as text, images, audio, or video, to help train artificial intelligence and machine learning models. Annotators manually or semi-automatically add metadata, such as identifying objects in images, transcribing speech, or categorizing text. This process improves AI accuracy by providing high-quality training data. Annotation work is crucial for industries like autonomous driving, healthcare, and natural language processing.

What are the typical projects or tasks an annotation specialist works on?

Annotation specialists typically work on projects involving the labeling and categorizing of data—such as images, videos, audio, or text—to train machine learning models. Weekly tasks may include reviewing raw data, applying specific tagging guidelines, performing quality checks on completed annotations, and collaborating with team members or machine learning engineers to ensure accuracy and consistency. Frequent feedback sessions and ongoing updates to annotation instructions are common as project requirements evolve. This role often requires close teamwork and clear communication within a collaborative environment, especially for large-scale or rapidly changing projects.

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

Excelling in an Annotation role generally requires keen attention to detail, strong analytical abilities, and a high level of accuracy, often backed by a relevant educational background. Familiarity with annotation tools, data labeling software, and sometimes basic programming or data management platforms is valuable. Effective time management, consistency, and clear communication are soft skills that differentiate top performers. These competencies are crucial to ensuring data quality and supporting the development of machine learning and AI systems.

What are annotation jobs?

Annotation jobs involve labeling or tagging data, such as images, text, or audio, to help train machine learning models. These roles often require attention to detail and familiarity with annotation tools or software, and they are commonly performed remotely or in a digital environment.

What skills are needed for annotation?

Annotation jobs require strong attention to detail, good reading comprehension, and the ability to follow specific guidelines. Familiarity with data labeling tools and basic computer skills are also important. Accuracy and consistency are essential for producing high-quality annotated data.

What are the most commonly searched types of Annotation jobs in Mountain View, CA?

The most popular types of Annotation jobs in Mountain View, CA are:

What job categories do people searching Annotation jobs in Mountain View, CA look for?

The top searched job categories for Annotation jobs in Mountain View, CA are:

What cities near Mountain View, CA are hiring for Annotation jobs?

Cities near Mountain View, CA with the most Annotation job openings:

Annotation jobs near you
Infographic showing various Annotation job openings in Mountain View, CA as of August 2026, with employment types broken down into 1% As Needed, 44% Full Time, 52% Part Time, 1% Temporary, and 2% Contract. Highlights an 36% Physical, 1% Hybrid, and 63% Remote job distribution, with an average salary of $68,911 per year, or $33.1 per hour.

Data Annotation Lead

Physical Intelligence

San Francisco, CA • On-site

$125 - $150/hr

Other

Re-posted 10 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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