Product Manager, AI/ML (Senior or Intermediate)

About Brainmaven

Brainmaven develops AI systems to enhance human decision-making under uncertainty. We are exploring new frontiers of the human-machine division of labor in terms of the provision of judgment and prediction and how these inputs are combined to make decisions. We apply our systems in enterprise settings. We continue to build our team with superstar individuals who are equally interested in this frontier.

Brainmaven is headquartered in Toronto, Canada.

About the Position

We are seeking a Product Manager (Senior or Intermediate) to manage a portfolio of products that leverage artificial intelligence and machine learning to address our clients’ most challenging business problems.

Responsibilities

• Understand clients’ business problems and identify possible technical solutions
• Develop comprehensive product requirement documents that include requirements for machine learning models, model integration, and user-facing software
• Work with technical teams to develop and manage a technical backlog and sprints
• Develop and maintain a prioritized roadmap of solutions to customer problems
• Coordinate with Brainmaven’s leadership team on a regular basis to ensure project success

Qualifications

• 3+ years experience building and shipping commercial software products through standard product management practices (defining requirements, managing a backlog and roadmap, etc.)
• 1+ years experience building and shipping products that leverage machine learning
• Proficient with standard product management tools (including JIRA)
• Proficient in Agile development methodologies
• Proficient in conveying technical concepts to non-technical people

Advantage if you have:

• Bachelor or Master degree in computer science, engineering, statistics, mathematics, or a related field
• 3+ years experience in management consulting or investment banking
• Proficiency with product analytics software (e.g., Amplitude)
• Proficiency with product design software (e.g., InVision)
• Familiarity with industry-standard frameworks and toolchains for implementing machine learning models in production