AI/ML Execution Program Manager
Tata Consultancy Services (TCS) · Oakland, US
Job description
-
We are seeking an experienced AI/ML Execution Program Manager to drive end-to-end execution of AI/ML initiatives across cross-functional teams. This role requires a strong blend of technical expertise in machine learning, data modeling, and dataset engineering, combined with program management excellence to deliver scalable AI solutions.
-
The ideal candidate will bridge the gap between data science, engineering, and business stakeholders, ensuring successful delivery of AI/ML programs—from problem definition and dataset modeling to model deployment and operationalization
Must Have Technical/Functional Skills:
-
Strong analytical and problem-solving skills
-
Ability to translate between technical and non-technical stakeholders
-
Excellent communication and stakeholder management
-
Data-driven decision-making mindset
-
Strong ownership and execution focus
Roles & Responsibilities:
- AI/ML Program Execution
-
Lead execution of AI/ML programs and projects from ideation through deployment and monitoring
-
Define program scope, milestones, deliverables, timelines, and success metrics
-
Drive alignment across data science, UI, API & data engineering, product, and business teams
-
Ensure adherence to ML lifecycle best practices (MLOps) including experimentation, model training, validation, and deployment
- Dataset Modeling & Data Strategy
-
Define and oversee dataset modeling strategies to support AI/ML use cases
-
Partner with data engineering teams to design:
-
Data schemas
-
Feature stores
-
Data pipelines and transformations
-
Ensure datasets are:
-
High-quality, labeled, and version-controlled
-
Representative and unbiased
-
Compliant with governance and privacy standards
Salary Range: $90,000 - $120,000 a year
#LI-CM2
Location
Santa Clara, CA
Job Function
TECHNOLOGY
Role
Program Manager
Job Id
416704
Desired Skills
Artificial Intelligence | Machine Learning | Program Management
Salary Range
$90,000-$120,000 a year
ML/AI Work links you to the employer's original posting — always verify the details there before applying.