
Program Manager
5 days ago
Designation : Program Manager
Experience – 10 – 15 years
Mode of employment – Full time Onsite
Key Responsibilities
Project Leadership:
Lead AI/ML projects from concept to execution, defining deliverables, roles, responsibilities, and project scope.
Technical Oversight:
Provide hands-on technical guidance, conduct code and solution reviews, and manage the development of AI/ML systems.
Team Management:
Supervise and mentor technical teams, fostering a collaborative environment for AI and data engineering.
Strategic Planning:
Develop and oversee project requirements, schedules, and roadmaps for AI/ML initiatives, aligning with business goals.
Cross-functional Collaboration:
Work closely with product management, data science, and engineering teams to define project strategies and integrate AI into products.
Technical Expertise:
Drive innovation in areas like foundation models, Generative AI (GenAI), Retrieval-Augmented Generation (RAG), and multi-modal LLMs.
Production Deployment:
Oversee the build-out of end-to-end ML systems for production, focusing on scalability, performance, and reliability.
Ethical AI:
Maintain a strong focus on responsible, transparent, and ethical AI practices throughout the project lifecycle.
Performance Monitoring:
Track project progress, key performance indicators (KPIs), and provide status reports to stakeholders and leadership.
Required Skills & Expertise
AI/ML Fundamentals:
Deep understanding of Machine Learning (ML), Deep Learning, and Natural Language Processing (NLP) concepts.
Programming & Data:
Proficiency in Python, SQL, and data manipulation libraries such as Pandas and NumPy.
AI Technologies:
Experience with Large Language Models (LLMs), foundation models, RAG, and prompt engineering.
Tools & Platforms:
Familiarity with AI experiment tracking tools like Weights & Biases and configuration management tools like Hydra.
Project Management:
Strong organizational skills, ability to multitask, and experience managing project schedules, scope, and budgets.
Leadership & Communication:
Proven ability to lead and inspire technical teams, communicate technical concepts to diverse stakeholders, and align AI initiatives with business objectives.
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