Senior Technical Program Manager (AI / ML projects)W2 Only

Senior Technical Program Manager (AI / ML projects) W2 only
Location: Hybrid Remote (Mountain View, or SF California, 2 days per week in office) (local candidates only!)

, or EAD

.. MUST HAVE'S .

Must have 6+ years of professional experience as a Technical Program Manager (previously an IT Project Manager) with a Bachelor's degree or related experience in AI / ML Program Management,

6+ 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.
Important!!! (Current 4+ years) 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.

As a Tech Program Manager - Advanced working SQL and dashboarding knowledge (Tableau or PowerBI or similar for data visualizations) Ability to build and maintain analytics to track, forecast, and visualize consumption through ad-hoc SQL, reports, and dashboards

Important - Project & Program Management overseeing projects dealing with large data sets, log data, ability to manage large data analytics projects, capacity planning and workflow management

Job Description:

The Client 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.

Program Ownership: Drive large-scale data annotation programs end-to-end, from scoping requirements to delivery and post-mortem analysis.
Cross-Functional Collaboration: Partner with AI Research leadership, AI researchers, data scientists, ML engineers, and product managers to define data needs, success metrics, and annotation guidelines.
Vendor & Workforce Management: Manage external annotation vendors and internal labeling teams, including contract negotiation, SLAs, quality standards, and throughput planning.
Quality & Process: Design and implement robust quality control pipelines, annotation tools, and feedback loops to ensure data quality at scale.
Tooling & Automation: Collaborate with engineering to improve annotation infrastructure, workflows, and data pipelines for efficiency and scalability.
Data Strategy & Governance: Contribute to data governance best practices, including privacy, security, ethics, and compliance in annotation workflows.
Reporting & Metrics: Define and track key program metrics (cost, quality, speed, volume), and regularly communicate progress to stakeholders and leadership.
Internal Adoption: Coordinate internal adoption of agentic AI products by building onboarding processes, workflows, and change management strategies.
Data Quality Leadership: Establish and standardize processes for measuring, monitoring, and improving data quality across datasets and annotation teams.
Customer Engagement: Collaborate with external customers and research partners on evaluation workshops, pilots, and feedback sessions to drive continuous improvement.

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.
Location is San Francisco, Mountain View or Seattle

Navnish kumar

Sr. IT Technical Recruiter

Stellent IT Phone:

Email: navnish
Gtalk: navnishom