AI/ML Program Manager with Agile experience
Apply NowCompany: InfiCare Software Technologies
Location: San Jose, CA 95123
Description:
Role-AI/ML Program Manager with Agile experience
Location : San Jose CA (Hybrid)
Skills and responsibilities:
Key Skills:
AI/ML Expertise: Understanding of machine learning lifecycle, model deployment, and data pipelines.
Agile & Scrum: Strong knowledge of Agile methodologies, sprint planning, backlog grooming, and working with cross-functional teams.
Project & Program Management: Experience in managing AI/ML projects end-to-end, including risk management, stakeholder communication, and resource allocation.
Technical Understanding: Familiarity with ML frameworks (TensorFlow, PyTorch), cloud platforms (AWS, GCP, Azure), and MLOps best practices.
Collaboration: Working closely with data scientists, engineers, and business stakeholders to ensure AI projects align with strategic goals.
Metrics & ROI Measurement: Defining key performance indicators (KPIs) for AI models and tracking their success post-deployment.
Responsibilities:
Leading AI/ML initiatives, ensuring they align with business objectives.
Managing cross-functional teams to develop and deploy AI solutions efficiently.
Facilitating Agile ceremonies (stand-ups, sprint reviews, retrospectives).
Ensuring AI/ML models are continuously improved and integrated into business processes.
Managing risks, dependencies, and compliance challenges in AI deployments.
Driving innovation by exploring new AI trends and methodologies.
Location : San Jose CA (Hybrid)
Skills and responsibilities:
Key Skills:
AI/ML Expertise: Understanding of machine learning lifecycle, model deployment, and data pipelines.
Agile & Scrum: Strong knowledge of Agile methodologies, sprint planning, backlog grooming, and working with cross-functional teams.
Project & Program Management: Experience in managing AI/ML projects end-to-end, including risk management, stakeholder communication, and resource allocation.
Technical Understanding: Familiarity with ML frameworks (TensorFlow, PyTorch), cloud platforms (AWS, GCP, Azure), and MLOps best practices.
Collaboration: Working closely with data scientists, engineers, and business stakeholders to ensure AI projects align with strategic goals.
Metrics & ROI Measurement: Defining key performance indicators (KPIs) for AI models and tracking their success post-deployment.
Responsibilities:
Leading AI/ML initiatives, ensuring they align with business objectives.
Managing cross-functional teams to develop and deploy AI solutions efficiently.
Facilitating Agile ceremonies (stand-ups, sprint reviews, retrospectives).
Ensuring AI/ML models are continuously improved and integrated into business processes.
Managing risks, dependencies, and compliance challenges in AI deployments.
Driving innovation by exploring new AI trends and methodologies.