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Manager Ai Annotation Jobs in California (NOW HIRING)

Sunday

Data Annotation Lead

Redwood City, CA · On-site

This role involves managing the people side of data annotations, creating processes, and ensuring ... to leverage AI to help improve productivity Company : Sunday is a robotics and artificial ...

Sunday Inc

Data Annotation Lead

Redwood City, CA · On-site

Manage the people side of data annotations * Create documentation * Be in the weeds and annotate ... Ability to leverage AI to help improve productivity At Sunday Robotics, we're building technology ...

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All JobsAi Annotation JobsManager Ai Annotation JobsManager Ai Annotation Jobs in California

Manager Ai Annotation information

What is the difference between Manager Ai Annotation vs Data Annotator?

AspectManager Ai AnnotationData Annotator
Required CredentialsBachelor's degree in related field, experience in AI projectsHigh school diploma or equivalent, on-the-job training
Work EnvironmentTeam management, project oversight, collaboration with data scientistsData labeling tasks, working with annotation tools
Industry UsageAI development, machine learning projectsData preparation for AI models
Search & Comparison IntentUnderstanding managerial roles in AI annotationEntry-level annotation tasks

The main difference between Manager Ai Annotation and Data Annotator lies in their responsibilities and experience. Managers oversee annotation projects, coordinate teams, and ensure quality, requiring leadership skills and experience. Data Annotators focus on labeling data accurately under supervision. Managers typically have higher credentials and work in strategic roles, while annotators perform the hands-on labeling tasks essential for AI training.

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Manager Ai Annotation jobs near you

Senior Technical Program Manager (AI/ML)

campus4tech

Mountain View, CA • On-site

Full-time

Posted 11 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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