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Data Annotation Project Manager Jobs in Mountain View, CA

Maxinsights

Technical Project Manager

Santa Clara, CA · On-site

Own the full lifecycle of complex robotics data collection and annotation projects--from initial ... Ensure dataset production meets strict client SLAs and accuracy standards while managing internal ...

Transformcap

Clinical Data Abstractor

San Mateo, CA · On-site

$80 - $100/hr

Support quality assurance initiatives, pilot annotation projects, and guidance and training ... Proven expertise in data privacy regulations (HIPAA) and data security best practices.

New

Welo Data

Lead Gen AI Analyst

Santa Clara, CA · On-site +1

$50/hr

... data annotation, content quality, Trust & Safety, data labeling, or similar production environments. * 3+ years of experience leading teams and managing projects , with ownership of delivery, quality ...

Specter

Data Operations Engineer

San Francisco, CA · On-site

$81K - $110K/yr

Define labeling taxonomies and annotation specifications Qualifications: * 1-3+ years of experience in data operations, project management, or a technical coordination role, ideally supporting ML or ...

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All JobsData Annotation Project JobsData Annotation Project Manager JobsData Annotation Project Manager Jobs in Mountain View, CA

Data Annotation Project Manager information

See Mountain View, CA salary details

$19

$67

$94

How much do data annotation project manager jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for data annotation project manager in Mountain View, CA is $67.84, according to ZipRecruiter salary data. Most workers in this role earn between $58.70 and $79.42 per hour, depending on experience, location, and employer.

What is a data annotation project manager?

A Data Annotation Project Manager is responsible for overseeing projects that involve labeling and categorizing data, such as images, text, or audio, to train machine learning models. They coordinate teams of annotators, manage project timelines, and ensure the quality and accuracy of the annotated data. This role often acts as a bridge between data scientists, clients, and annotation teams, ensuring project requirements are met efficiently and effectively.

What are the key skills and qualifications needed to thrive as a data annotation project manager?

To thrive as a Data Annotation Project Manager, you need strong project management skills, a solid understanding of data annotation processes, and experience with quality assurance, often supported by a degree in a relevant field. Familiarity with annotation tools (like Labelbox or Supervisely), workflow management platforms, and sometimes agile or PMP certification is highly beneficial. Exceptional communication, attention to detail, and leadership abilities help you effectively coordinate teams and ensure project deliverables meet quality standards. These skills are essential for managing complex annotation projects efficiently, maintaining data integrity, and supporting successful machine learning outcomes.

What are some common challenges faced by data annotation project managers, and how can they be managed effectively?

One of the primary challenges Data Annotation Project Managers face is ensuring high-quality, consistent labeling across large and sometimes distributed annotation teams. Managing tight deadlines while maintaining annotation accuracy requires effective training, clear guidelines, and regular quality checks. Additionally, balancing communication between data scientists, clients, and annotators is crucial to align expectations and resolve ambiguities quickly. Successful managers often implement robust feedback loops, leverage annotation tools with built-in quality control features, and foster an open environment for continuous improvement.

What is the difference between Data Annotation Project Manager vs Data Labeling Specialist?

AspectData Annotation Project ManagerData Labeling Specialist
CredentialsTypically requires project management experience, certifications in data management or related fieldsOften requires basic technical skills, familiarity with labeling tools, sometimes certifications in data annotation
Work EnvironmentOversees teams, manages projects, coordinates workflows in office or remote settingsPerforms labeling tasks, often in a remote or on-site environment, focused on data tagging
Employer & Industry UsageUsed by tech companies, AI firms, and data service providers for managing annotation projectsEmployed within similar industries, focusing on executing labeling tasks under supervision

The main difference is that the Data Annotation Project Manager oversees and coordinates annotation projects, ensuring quality and deadlines, while the Data Labeling Specialist focuses on executing the labeling tasks themselves. Both roles are essential in the data annotation process but differ in responsibilities and scope.

What are popular job titles related to Data Annotation Project Manager jobs in Mountain View, CA?

For Data Annotation Project Manager jobs in Mountain View, CA, the most frequently searched job titles are:

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

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

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

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

Data Annotation Project Manager jobs near you
Infographic showing various Data Annotation Project Manager job openings in Mountain View, CA as of August 2026, with employment types broken down into 79% Full Time, 9% Part Time, and 12% Contract. Highlights an 76% In-person, 4% Hybrid, and 20% Remote job distribution, with an average salary of $141,110 per year, or $67.8 per hour.

Senior Technical Program Manager (AI/ML)

campus4tech

Mountain View, CA • On-site

Full-time

Re-posted 21 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.

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