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Lila Sciences

Technical Program Manager, AI Data

Cambridge, MA · On-site +1

$141K - $182K/yr

You don't need to be an ML researcher, but you must be genuinely curious about how AI data fuels ... Experience managing programs that produce standardized outputs for downstream technical consumers ...

Motorola

$127K - $165K/yr

Drive strategic programs to integrate AI/ML into our internal software development lifecycle ... Qualifications & Experience * 10+ years of technical program management experience, with ...

Google

Technical Program Manager, NPI, AI/ML

Sunnyvale, CA · On-site

$151K - $196K/yr

As a Technical Program Manager at Google, you'll use your technical expertise to lead complex ... The AI and Infrastructure team is redefining what's possible. We empower Google customers with ...

Apple

Sr Engineering Program Manager, AI/ML

Cupertino, CA · On-site

$159K/yr

The Graphics, Gaming & Machine Learning (GGML) team is seeking a Technical Program Manager to help ... Experience leading multi-functional teams to develop and deploy GPU-accelerated AI/ML solutions ...

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How much do technical program manager ai ml jobs pay per year?

As of Jun 11, 2026, the average yearly pay for technical program manager ai ml in the United States is $145,648.00, according to ZipRecruiter salary data. Most workers in this role earn between $129,000.00 and $167,000.00 per year, depending on experience, location, and employer.
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Senior Technical Program Manager (AI/ML)

campus4tech

Mountain View, CA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

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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