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Data Annotation Program Manager Jobs (NOW HIRING)

Data Annotation Project Manager

Cupertino, CA · Hybrid

$63.75 - $86.25/hr

... data annotation projects. In this role, you will help drive projects forward, ensure clear ... Required Skills & Qualifications * 5-10 years of experience managing cross-functional programs or ...

Required Skills & Qualifications * 5 years in operations, project management, or data analysis ... Find, socialize, and implement program improvements in coordination with stakeholders. * Facilitate ...

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Data Annotation Program Manager information

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$31K

$97.1K

$172K

How much do data annotation program manager jobs pay per year?

As of Jun 3, 2026, the average yearly pay for data annotation program manager in the United States is $97,145.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,000.00 and $125,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Annotation Program Manager, and why are they important?

To thrive as a Data Annotation Program Manager, you need expertise in project management, data quality assessment, and a solid understanding of machine learning or data annotation processes, typically supported by a relevant degree. Familiarity with annotation platforms, workflow management tools, and data labeling software is essential, along with knowledge of quality assurance frameworks. Strong leadership, problem-solving abilities, and effective communication are crucial soft skills that help manage diverse teams and ensure stakeholder alignment. These skills are important to maintain high data quality, meet project deadlines, and drive successful AI model training initiatives.

How does a Data Annotation Program Manager coordinate with cross-functional teams to ensure project success?

A Data Annotation Program Manager regularly collaborates with engineering, data science, and quality assurance teams to align annotation guidelines, project timelines, and quality standards. They often facilitate meetings to clarify requirements, resolve ambiguities in data labeling, and provide feedback on annotation accuracy. This role serves as a bridge between technical teams and annotation staff, ensuring open communication and timely resolution of challenges, which is critical for delivering high-quality datasets essential for machine learning and AI projects.

What are Data Annotation Program Managers?

Data Annotation Program Managers are professionals who oversee and coordinate data labeling projects, ensuring that data used for machine learning and artificial intelligence is accurately tagged and prepared. They manage teams of annotators, set project guidelines, monitor quality, and ensure deadlines are met. Their role is crucial for building high-quality datasets that enable reliable AI model training. Program Managers often collaborate with data scientists, engineers, and stakeholders to define requirements and improve annotation processes.
More about Data Annotation Program Manager jobs
What cities are hiring for Data Annotation Program Manager jobs? Cities with the most Data Annotation Program Manager job openings:
What states have the most Data Annotation Program Manager jobs? States with the most job openings for Data Annotation Program Manager jobs include:
Infographic showing various Data Annotation Program Manager job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, and 99% Full Time. Highlights an 46% Physical, 1% Hybrid, and 53% Remote job distribution, with an average salary of $97,145 per year, or $46.7 per hour.

Senior Technical Program Manager (AI/ML)

campus4tech

Mountain View, CA • On-site

Full-time

Posted 19 days ago


Job description

Job Title- Senior Technical Program Manager (AI/ML)
Location- Mountain View, CA, United States, 94041
Reporting Type- Onsite
Duration: 11 Months
W2 candidates only for this role
Summary
The Client's R&D Operations Organization is seeking a highly motivated and technically skilled Technical Program Manager (TPM) to lead and oversee data annotation programs that power our cutting-edge AI research initiatives. This role sits at the intersection of program management, data operations, and AI/ML, and will play a pivotal part in ensuring that our data annotation efforts are scalable, high-quality, and aligned with the needs of our research and product teams.
You will collaborate closely with researchers, data scientists, ML engineers, and vendor operations to drive the end-to-end lifecycle of large-scale data labeling and curation efforts - from strategy and planning to execution, delivery, and quality evaluation.
Requirements
  • Bachelor's or Master's degree in a technical field (e.g. Computer Science, Data Science, Machine Learning, Information Systems) or equivalent practical experience.
  • 7+ years of experience in technical program management, project management, or operations in data-centric or AI/ML environments.
  • Strong understanding of ML development workflows, data pipelines, and annotation lifecycle.
  • Experience managing large-scale data labeling or data collection efforts, including working with third-party vendors.
  • Familiarity with big data platforms (e.g. Apache Spark, Databricks, Hadoop) and data warehousing concepts.
  • Excellent organizational, problem-solving, and communication skills with the ability to influence cross-functional stakeholders.
  • Proven track record of driving cross-functional teams to deliver complex technical projects on time and with high quality.
  • Excellent communication, negotiation and analytical skills, with the ability to document standard operating procedures and processes
  • Advanced working SQL Knowledge, Ability to build and maintain analytics to track, forecast, and visualize consumption through ad-hoc SQL, reports, and dashboards
  • Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
  • Self-motivated and able to work independently, as well as in a team environment.
  • Preferred good working knowledge of GPU technology and its applications in generative AI and machine learning.
  • Familiarity with big data technologies such as Apache Spark, Delta Lake, and MLflow is a plus.