AI/ML Product Manager (WFH)

Job Summary:

The AI/ML Product Manager will be responsible for guiding the development and deployment of artificial intelligence and machine learning-based products. This role combines technical expertise in AI/ML with strong product management skills to deliver solutions that meet business needs and customer expectations. The ideal candidate will have a deep understanding of AI/ML technologies and experience managing product lifecycles from ideation through launch, working closely with cross-functional teams including data scientists, engineers, and business stakeholders.

Key Responsibilities:

• Product Strategy: Define the product vision and strategy for AI/ML-

  powered products, aligning them with overall business objectives and market opportunities. Oversees the development and implementation of AI-driven products, ensuring they meet market needs.

• Roadmap Development: Develop and maintain a product roadmap, prioritizing features and functionalities that deliver value to customers while leveraging AI/ML technologies.
• Cross-functional Collaboration: Work closely with engineering, data science, and design teams to ensure the successful development and deployment of AI/ML models and features.
• Customer Research: Conduct market research, gather customer feedback, and analyze user data to identify product opportunities, pain points, and improvements.
• Requirements Gathering: Define product requirements, user stories, and acceptance criteria, ensuring clarity for development teams and alignment with business goals.
• Model Lifecycle Management: Collaborate with machine learning engineers and data scientists to oversee the full lifecycle of AI/ML models, from experimentation and development to deployment and monitoring.
• Performance Monitoring: Establish and track key performance indicators (KPIs) and metrics to measure the effectiveness of AI/ML models and product features, iterating as necessary.
• Product Launches: Plan and execute product launches, ensuring that cross-functional teams are prepared, and customers are informed of new features and capabilities.
• Stakeholder Communication: Communicate progress, insights, and challenges to key stakeholders, including executive leadership, technical teams, and clients.
• Ethics and Compliance: Ensure that AI/ML products comply with relevant ethical guidelines, data privacy regulations, and industry standards.
• Innovation & Trends: Stay current with the latest AI/ML advancements, emerging technologies, and industry trends, bringing fresh ideas to the product development process.

Qualifications:

• Education: Bachelor’s or Master’s degree in Computer Science, Data 

  Science, Engineering, Business Administration, or a related field. A technical degree is highly preferred.
• Experience:
  • 3+ years of experience in product management, with a focus on AI/ML or data-driven products.
  • Proven track record of managing AI/ML product lifecycles from concept to launch.
  • Strong technical understanding of AI/ML technologies and how they can be applied to solve real-world problems.
  • Hands-on experience working with data science and engineering teams.

  • Experience with agile development methodologies.

• Skills:
  • Strong project management skills, with the ability to prioritize tasks and manage time effectively.
  • Excellent communication skills, capable of conveying complex technical concepts to both technical and non-technical audiences.
  • Proficiency with product management tools such as Jira, Trello, or Asana.
  • Familiarity with AI/ML tools and platforms like TensorFlow, PyTorch, or AWS SageMaker.
  • Strong analytical and problem-solving skills.
  • Ability to balance short-term product deliverables with long-term strategic goals.
  • Requires a blend of technical knowledge and business acumen.

Preferred Qualifications:

• Experience in industries that are heavy users of AI/ML such as healthcare, finance, e-commerce, or autonomous systems.
• Experience with data governance, AI ethics, and machine learning model interpretability.
• Knowledge of cloud platforms (AWS, GCP, Azure) and MLOps practices.

• MBA or advanced degree in a relevant field.