AI/ML Technical Project Manager

Nityo Infotech Limited; Santa Clara (CA); On-site; USD 170,000 - 210,000; Full time

Job summary

Nityo Infotech Limited seeks a strategic AI/ML program leader to drive initiatives from ideation through deployment and monitoring in Santa Clara, CA. You will define scope, goals, timelines, budgets, and success metrics, aligning AI solutions with business objectives and technical standards.

You will coordinate data science, engineering, product, legal, security, and compliance, develop roadmaps, manage risks, and communicate progress to leadership.

Responsibilities

• Lead end-to-end delivery of AI/ML programs from ideation through deployment and post-production monitoring.
• Define program scope, goals, timelines, budgets, and success metrics.
• Coordinate cross-functional teams including data science, engineering, product, legal, security, and compliance.
• Develop and maintain detailed project plans, roadmaps, and risk registers.
• Track dependencies, milestones, and deliverables across multiple workstreams.
• Ensure AI solutions align with business objectives and technical architecture standards.
• Manage stakeholder communication and provide regular status updates to leadership.
• Identify and mitigate risks related to data quality, model performance, governance, and compliance.
• Drive adoption of responsible AI practices, including fairness, transparency, and explainability.
• Monitor production KPIs such as model accuracy, latency, drift, and ROI.
• Facilitate vendor management and coordination with external partners when needed.
• Support change management, user training, and rollout activities.

Job description

• Lead end-to-end delivery of AI/ML programs, from ideation through deployment and post-production monitoring.
• Define program scope, goals, timelines, budgets, and success metrics.
• Coordinate cross-functional teams including data science, engineering, product, legal, security, and compliance.
• Develop and maintain detailed project plans, roadmaps, and risk registers.
• Track dependencies, milestones, and deliverables across multiple workstreams.
• Ensure AI solutions align with business objectives and technical architecture standards.
• Manage stakeholder communication and provide regular status updates to leadership.
• Identify and mitigate risks related to data quality, model performance, governance, and compliance.
• Drive adoption of responsible AI practices, including fairness, transparency, and explainability.
• Monitor production KPIs such as model accuracy, latency, drift, and ROI.
• Facilitate vendor management and coordination with external partners when needed.
• Support change management, user training, and rollout activities.