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Annotation Math Jobs in Santa Clara, CA (NOW HIRING)

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Helix AI Engineer, Perception

San Jose, CA · On-site

... annotation. • Own the end-to-end product life cycle from initial ideation to deployment. • ... Strong mathematical foundation in probability, optimization, and linear algebra. • Domain ...

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Helix AI Engineer, Perception

San Jose, CA · Hybrid

$200K - $400K/yr

... offline data annotation. * Own the end-to-end product life cycle from initial ideation to ... Strong mathematical foundation in probability, optimization, and linear algebra. * Domain expertise ...

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Helix AI Engineer, Perception

San Jose, CA · On-site

$200K - $400K/yr

... offline data annotation. * Own the end-to-end product life cycle from initial ideation to ... Strong mathematical foundation in probability, optimization, and linear algebra. * Domain expertise ...

Nexxa.ai

AI Vision Engineer

Sunnyvale, CA · On-site

$120 - $190/hr

Build scalable data pipelines for image and video collection, annotation, augmentation, training ... Mathematics, Statistics, Artificial Intelligence, or a related technical field, or equivalent ...

Abbott

Senior Staff AI/ML Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

Work on end-to-end ML solutions development and delivery, including data ingestion, annotation ... Bachelors Degree in Computer Science, Engineering Mathematics, or related field. * Minimum 8+ years ...

Abbott

Senior Staff ML Ops Engineer

Santa Clara, CA · On-site

$121K - $167K/yr

... annotation, feature engineering, training, validation, deployment, and monitoring. * Engage ... Bachelors Degree in Computer Science, Engineering Mathematics, or related field. * Minimum 8+ years ...

New

Abbott

Senior Staff AI/ML Engineer

Santa Clara, CA · On-site

$121K - $167K/yr

Work on end-to-end ML solutions development and delivery, including data ingestion, annotation ... Bachelors Degree in Computer Science, Engineering Mathematics, or related field. * Minimum 8+ years ...

Abbott

Senior Staff AI/ML Engineer

Santa Clara, CA · On-site

$121K - $167K/yr

Work on end-to-end ML solutions development and delivery, including data ingestion, annotation ... Bachelors Degree in Computer Science, Engineering Mathematics, or related field. * Minimum 8+ years ...

Abbott

Senior Staff ML Ops Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

BachelorsDegreein Computer Science, Engineering Mathematics, or related field. * Minimum8+ years of ... annotation tools,model serving,monitoringand observability. * Experience with GenAI and Agentic AI ...

Abbott

Senior Staff ML Ops Engineer

Santa Clara, CA · On-site

$121K - $167K/yr

... annotation, feature engineering, training, validation, deployment, and monitoring. * Engage ... Bachelors Degree in Computer Science, Engineering Mathematics, or related field. * Minimum 8+ years ...

New

Abbott

Senior Staff ML Ops Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

BachelorsDegreein Computer Science, Engineering Mathematics, or related field. * Minimum8+ years of ... annotation tools,model serving,monitoringand observability. * Experience with GenAI and Agentic AI ...

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Showing results 21-40

All JobsAnnotation Math JobsAnnotation Math Jobs in Santa Clara, CA

Annotation Math information

See Santa Clara, CA salary details

$26.4K

$69.1K

$111K

How much do annotation math jobs pay per year?

As of Sep 4, 2026, the average yearly pay for annotation math in Santa Clara, CA is $69,101.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,800.00 and $82,200.00 per year, depending on experience, location, and employer.

What is an annotation math job?

Annotation Math jobs involve labeling, tagging, and categorizing mathematical data, such as equations, formulas, graphs, or written math problems, to create high-quality datasets. These annotated datasets are often used to train artificial intelligence (AI) and machine learning models to recognize and process mathematical content accurately. Annotation Math professionals need a strong understanding of mathematics, attention to detail, and familiarity with annotation tools or platforms. This work is critical for improving technologies like automated math solvers, educational apps, and document digitization.

What are some common challenges faced by professionals in annotation math roles, and how can they be addressed?

Professionals in Annotation Math roles often encounter challenges such as interpreting ambiguous mathematical data, maintaining consistency in labeling complex equations, and managing repetitive tasks that require high attention to detail. Addressing these challenges involves following clear annotation guidelines, collaborating with team members to resolve uncertainties, and utilizing quality assurance tools to minimize errors. Regular feedback sessions and ongoing training also help ensure accuracy and support professional growth in this specialized field.

What are the key skills and qualifications needed to thrive as an annotation math specialist, and why are they important?

To thrive as an Annotation Math Specialist, you need a solid understanding of mathematics, attention to detail, and familiarity with educational or assessment standards, often supported by a relevant degree. Proficiency with annotation tools, data labeling platforms, and sometimes LaTeX or similar mathematical typesetting systems is typically required. Strong analytical thinking, communication, and the ability to work independently are essential soft skills for accuracy and consistency. These skills and qualities are crucial to ensure high-quality, precise annotations that support machine learning, educational resources, or assessment development.

What is the difference between Annotation Math vs Data Annotator?

AspectAnnotation MathData Annotator
Required CredentialsBasic education, sometimes specialized training in annotation toolsHigh school diploma or equivalent, on-the-job training
Work EnvironmentData labeling teams, tech companies, remote or onsiteData labeling teams, tech companies, remote or onsite
Industry UsageAI, machine learning, data scienceAI, machine learning, data science
Common Search IntentUnderstanding roles related to data annotation and mathComparing data annotation jobs

Annotation Math and Data Annotator roles both involve data labeling within AI and machine learning industries. Annotation Math may focus more on mathematical annotations, while Data Annotator generally covers broader data labeling tasks. Both roles often share similar work environments and required skills, making them closely related in the data annotation field.

What are popular job titles related to Annotation Math jobs in Santa Clara, CA?

For Annotation Math jobs in Santa Clara, CA, the most frequently searched job titles are:

What job categories do people searching Annotation Math jobs in Santa Clara, CA look for?

The top searched job categories for Annotation Math jobs in Santa Clara, CA are:

What cities near Santa Clara, CA are hiring for Annotation Math jobs?

Cities near Santa Clara, CA with the most Annotation Math job openings:

Annotation Math jobs near you
Infographic showing various Annotation Math job openings in Santa Clara, CA as of August 2026, with employment types broken down into 72% Full Time, 25% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 97% Physical, and 3% Remote job distribution, with an average salary of $69,101 per year, or $33.2 per hour.

Machine Learning PhD Student Contributor

Cobalt

Santa Clara, CA • On-site

Other

Posted 4 days ago

Key responsibilities

  • Produce written reasoning traces on complex ML problems and draft expert reference answers to technical questions.

  • Evaluate model-generated technical content by comparing responses, articulating strengths, and identifying points of failure in reasoning.

  • Assess whether conclusions are supported by derivations, code, or experimental evidence, and contribute to designing scoring rubrics and benchmark datasets.

Job description

About the role:

Cobalt is seeking PhD-qualified machine learning researchers with direct experience designing, running, and evaluating original ML research. This opportunity is suited to researchers who have worked in academic ML labs, industry research groups, or frontier lab environments, and who understand how technical claims are established, tested, and supported by evidence.

You may currently work, or have previously worked, as a PhD candidate, Postdoctoral Researcher, Research Scientist, Research Engineer, Applied Scientist, Member of Technical Staff, or in a related role.

You do not need prior experience in data annotation or model evaluation. You must, however, have contributed meaningfully to at least one substantive ML research output, and you must be comfortable reading papers, interpreting experimental results, and judging whether stated conclusions follow from the underlying evidence.


What you'll do:

Depending on the project, you may:

  • Produce written reasoning traces on hard ML problems, capturing how you reach a solution rather than only the solution itself, and draft expert reference answers to technical questions
  • Author novel problems in your subfield that have verifiable or defensible correct answers
  • Evaluate model-generated technical content: compare and rank responses, articulate what makes the stronger one stronger, and identify the specific step at which a chain of reasoning breaks down
  • Assess whether stated conclusions are supported by the underlying derivation, code, or experimental evidence
  • Design rubrics and partial-credit criteria for scoring multistep technical tasks, and contribute subject-matter expertise to benchmark and dataset development

Projects follow their own annotation guidelines and quality standards, and you will work with feedback from reviewers and lab research teams.


Required qualifications:

  • PhD, completed or in progress, in machine learning, computer science, statistics, mathematics, physics, or a closely related quantitative discipline, with research that is substantially ML focused
  • Direct experience authoring, co-authoring, or substantively contributing to at least one ML research output, such as a peer-reviewed paper, preprint, thesis chapter, or comparable technical artifact
  • Demonstrated depth in at least one area, for example optimization, reinforcement learning, language model training and post-training, learning theory, probabilistic methods, computer vision, natural language processing, or systems for ML
  • Ability to interpret papers, derivations, code and experimental results, and to explain your reasoning clearly in writing
  • Strong attention to detail, a commitment to factual accuracy, and the ability to work independently to agreed timelines


Why join Cobalt AI:

  • Advance frontier AI where it counts. Apply your research expertise to the data that frontier labs cannot obtain any other way, where your reasoning directly shapes how the next generation of models works through technical problems.
  • Grow professionally. Expand your influence through evaluation projects, advisory roles, and research collaborations, while deepening your understanding of how frontier models are trained and assessed.
  • Work with a top-tier network. Collaborate with researchers from leading institutions and labs on high-impact, flexible work.
  • Set your own schedule. Flexible 10 to 40 hour weeks that fit around your research position and your life.
  • Competitive pay. Rates vary by project and are determined by a number of factors, including scope, skillset, and experience.

Apply