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Annotation Program Manager Jobs (NOW HIRING)

Technical Program Manager III

Mountain View, CA · On-site

$152K - $197K/yr

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 ...

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 ...

About the Role We are seeking a Senior Technical Program Manager to lead Sesame's data collection ... Lead audio data collection and annotation efforts at Sesame. * Collaborate with research and ...

Technical Program Manager

San Francisco, CA · On-site

$152K - $196K/yr

... to annotation to delivery. We design and create datasets from scratch, recruit and manage the ... Track record managing complex, multi-stakeholder enterprise programs * Metrics-driven: owns and ...

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Annotation Program Manager information

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$38.5K

$107.5K

$157K

How much do annotation program manager jobs pay per year?

As of Jul 7, 2026, the average yearly pay for annotation program manager in the United States is $107,460.00, according to ZipRecruiter salary data. Most workers in this role earn between $79,500.00 and $132,500.00 per year, depending on experience, location, and employer.

Technical Program Manager III

campus4tech

Mountain View, CA • On-site

$152K - $197K/yr

Full-time

Re-posted 11 days ago


Job description

Job Title: Technical Program Manager III
Location: Bellevue, WA/Seattle, WA/San Francisco, CA/ Mountain View, CA
Job Mode: Onsite
Contract Duration: 12 months
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.
Requirement:
  • 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.