Associate Project Manager – AI/ML

Associate Project Manager – AI/ML

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🔍 Job Summary

We are seeking experienced Associate Project Managers with a strong foundation in AI/ML project delivery. The ideal candidate will have a proven track record of managing cross-functional teams, delivering complex software projects, and driving AI/ML initiatives from conception to deployment. This role requires a blend of project management expertise and technical understanding of machine learning systems, data pipelines, and model lifecycle management.

✅ Required Experience & Skills

📌 Project Management

• Minimum 3+ years of project management experience, including planning, tracking, and delivering software projects.
• Strong experience in Agile, Scrum, and SDLC/Waterfall methodologies.
• Proven ability to manage multiple projects and stakeholders across business and technical teams.
• Experience in budgeting, vendor negotiation, and resource planning.
• Proficiency in tools like MS Project, Excel, PowerPoint, ServiceNow, SmartSheet, and Lucidchart.

🤖 AI/ML Technical Exposure (Must-Have)

• Exposure to AI/ML project lifecycle: data collection, model development, training, validation, deployment, and monitoring.
• Understanding of ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and data platforms (e.g., Azure ML, AWS SageMaker, Databricks).
• Familiarity with MLOps practices, model versioning, and CI/CD pipelines for ML.
• Experience working with data scientists, ML engineers, and DevOps teams to deliver AI/ML solutions.
• Ability to translate business problems into AI/ML use cases and manage delivery timelines.

🧩 Leadership & Communication

• Strong leadership, decision-making, and organizational skills.
• Excellent communication and stakeholder management abilities.
• Ability to influence and gain buy-in from executive sponsors and cross-functional teams.
• Experience in building and maintaining relationships with business leaders and technical teams.

🎯 Roles & Responsibilities

• Lead AI/ML and software development projects from initiation through delivery.
• Collaborate with data science and engineering teams to define project scope, milestones, and deliverables.
• Develop and maintain detailed project plans aligned with business goals and technical feasibility.
• Monitor progress, manage risks, and ensure timely delivery of AI/ML models and software components.
• Coordinate cross-functional teams and ensure alignment between business, data, and engineering stakeholders.
• Track project metrics, ROI, and model performance post-deployment.
• Ensure compliance with data governance, security, and ethical AI standards.
• Drive continuous improvement in project execution and delivery frameworks.
• Stay updated on AI/ML trends and contribute to strategic planning for future initiatives.