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Annotation Math Jobs in Albany, CA (NOW HIRING)

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Annotation Math information

See Albany, CA salary details

$26.3K

$68.8K

$110.5K

How much do annotation math jobs pay per year?

As of Jun 10, 2026, the average yearly pay for annotation math in Albany, CA is $68,824.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,600.00 and $81,900.00 per year, depending on experience, location, and employer.

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 Annotation Math jobs?

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 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 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 job categories do people searching Annotation Math jobs in Albany, CA look for? The top searched job categories for Annotation Math jobs in Albany, CA are:
What cities near Albany, CA are hiring for Annotation Math jobs? Cities near Albany, CA with the most Annotation Math job openings:
Annotation Math jobs near you
Forward Deployed Engineer Intern

Forward Deployed Engineer Intern

Labelbox

San Francisco, CA • On-site

Internship

Posted 11 days ago

Job description

Shape the Future of AI
At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially.
About Labelbox
We're the only company offering three integrated solutions for frontier AI development:
  1. Enterprise Platform & Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale
  2. Frontier Data Labeling Service: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models
  3. Expert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling
Why Join Us
  • High-Impact Environment: We operate like an early-stage startup, focusing on impact over process. You'll take on expanded responsibilities quickly, with career growth directly tied to your contributions.
  • Technical Excellence: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence.
  • Innovation at Speed: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution.
  • Continuous Growth: Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI.
  • Clear Ownership: You'll know exactly what you're responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics.

About the role
As a Forward Deployed Engineer Intern, you will work alongside a senior FDE on real client engagements with leading AI labs. You will own concrete pieces of those engagements - writing scripts to process and analyze data, building automated quality checks, and helping validate that the data we deliver is good enough to ship. The work is hands-on, fast-paced, and rarely arrives with a complete spec.
This is not a shadowing internship. You will be expected to take ownership of your projects, work through ambiguity with your manager, and ship work that real clients depend on. If you do well, you will see your work translate directly into how frontier AI models are trained and evaluated.
About Labelbox
Labelbox builds the data infrastructure behind frontier AI development. We work with leading research labs and enterprises to produce the high-quality datasets used for evaluation, supervised fine-tuning, and reinforcement learning. The Frontier AI team you will be joining sits at the intersection of engineering and applied research, working directly with AI lab partners on some of the most demanding data problems in the industry.
What you'll do
  • Work alongside a senior FDE on live client engagements, owning specific workstreams end-to-end.
  • Write scripts to process, transform, and analyze data for client deliverables.
  • Build automated quality checks and serve as a second set of eyes on the data we ship.
  • Take ambiguous, partially-defined requirements and turn them into something concrete.
  • Read existing code, extend it, and improve it - most of what you build will plug into systems that already exist.
  • Drive your work forward without needing daily check-ins. Proactively share progress, flag blockers, and ask for input when you need it.
What we're looking for
We care more about how you think than about a specific list of credentials. The things below are what tend to make interns successful in this role:
  • Strong Python skills, especially for data work. You should be comfortable picking up a messy dataset and figuring out what is in it.
  • Familiarity with LLMs from hands-on experience, not just coursework. You have built something with them and have iterated on prompts to make them do what you want.
  • Strong analytical thinking. You can look at data, spot what is off, and ask the right questions about whether a result is real or noise.
  • Strong written and verbal communication. You can write a clear update, explain technical work to non-technical stakeholders, and ask a well-formed question when you are stuck.
  • You finish what you start. When you take on a task, you see it through to the end - including the parts that are not interesting.
  • Fast learner. The tools, frameworks, and benchmarks you will encounter change quickly. You pick them up without being walked through them.
  • High agency and ownership. You take responsibility for your work, push it forward without being prompted, and flag issues early rather than late.
Who you are
  • Currently pursuing a Bachelor's or Master's in Computer Science, Engineering, Mathematics, or a related technical field.
  • Genuinely curious about AI and how frontier models are built.
  • You like being the person who turns "we should look into this" into something concrete.
  • You work independently and communicate generously. You move fast on your own.
  • Receptive to feedback.
Why this role
FDE work at Labelbox is a spot where it spans engineering, research, and direct client work. As an intern, you will get exposure to all three - and to the kinds of problems that most engineering internships do not touch. You will work with people who care about getting the technical details right and who will give you the room to do the same.
Compensation
This is a paid internship with an hourly rate of $50-$70 per hour.
Life at Labelbox
  • Location: Join our dedicated tech hubs in San Francisco or Wrocław, Poland
  • Work Style: Hybrid model with 2 days per week in office, combining collaboration and flexibility
  • Environment: Fast-paced and high-intensity, perfect for ambitious individuals who thrive on ownership and quick decision-making
  • Growth: Career advancement opportunities directly tied to your impact
  • Vision: Be part of building the foundation for humanity's most transformative technology
Our Vision
We believe data will remain crucial in achieving artificial general intelligence. As AI models become more sophisticated, the need for high-quality, specialized training data will only grow. Join us in developing new products and services that enable the next generation of AI breakthroughs.
Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins. Our customers include Fortune 500 enterprises and leading AI labs.
Your Personal Data Privacy: Any personal information you provide Labelbox as a part of your application will be processed in accordance with Labelbox's Job Applicant Privacy notice.
Any emails from Labelbox team members will originate from a @labelbox.com email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications.

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