AI Project Manager (remote)

Responsibilities

• Project Lifecycle Management: Plan and oversee all stages of AI-led creative projects, from ideation and data collection to delivery, as well as model training, monitoring, and reporting.
• Cross-Functional Partnerships: Act as a critical bridge between highly technical teams, creative teams, and business/marketing stakeholders, ensuring seamless project delivery, resource optimization, and robust controls adherence through ongoing communication.
• Work across and coordinate diverse, cross-functional teams for the purpose of creative delivery, including AI technologists, prompt engineers, brand managers, and creatives.
• Foster a collaborative environment and help resolve conflicts.
• Strategic Planning and Alignment: Define project scope, objectives, and success metrics for AI-powered deliverables. Ensure AI solutions provide measurable business value and align with the company's overall strategic goals.
• Serve as the primary liaison between brand management and creative teams, translating complex AI concepts into clear, actionable business insights.
• Risk and Quality Management: Work with creative technologists and prompt engineers to proactively identify, assess, and mitigate risks, including those related to timeline and execution, data quality, model bias, or ethical concerns. Ensure AI solutions meet high-quality and regulatory standards.
• Budget and Resource Management: Create and manage project budgets, track expenditures, and allocate resources effectively to ensure projects run smoothly. Ensure AI initiatives align with business objectives and are delivered on time, within scope, and on budget.
• Continuous Learning: Stay up-to-date with emerging AI trends, tools, and platforms to ensure project relevance and foster a culture of continuous improvement.

Qualifications

• 3 or more years of project management experience, with a proven track record of successfully delivering AI/ML projects.
• Proficient in project planning, risk management, and stakeholder management.
• Deep understanding of (or the ability to learn and master quickly) creative workflows and controls, as well as AI methodologies, data management, and ethical considerations related to using AI technologies.
• Strong understanding of AI/ML concepts, such as natural language processing (NLP), deep learning, and data science principles.
• Understanding of data's role in AI, including data quality, pipelines, and data-driven decision-making.
• Excellent leadership, communication, and problem-solving abilities. Must be adaptable, results-oriented, and able to manage complex, ambiguous projects.