Technical Product Manager (AI)

Location: Based in, or willing to relocate to, Austin, TX or Los Angeles, CA, US

Company

hirify.global develops virtual-reality and sports-training products for baseball and softball players, combining software, computer vision, AI, cameras, sensors, and data.

What you will do

• Own the roadmap for sports data products covering ball and player tracking, swing and pitch metrics, and AI-driven insights.
• Write technical requirements for accuracy, latency, data schemas, and APIs.
• Partner with computer vision, AI, hardware, and backend engineering teams; define evaluation criteria and validate data quality against ground truth.
• Make trade-off decisions across accuracy, cost, and timelines.
• Understand data needs from players, coaches, teams, and analysts and translate raw data into useful training insights.
• Run cross-functional programs across hardware, firmware, computer vision, cloud, and apps, including plans, dependencies, milestones, status, and risks.

Requirements

• 4+ years of product management experience with technical products involving data, AI/ML, computer vision, or hardware.
• Engineering background through a degree in Computer Science, Electrical Engineering, or a related field, or prior experience as an engineer.
• Working fluency in computer vision and machine learning concepts.
• Program management experience across hardware and software teams.
• Strong interest in sports; baseball or softball experience is ideally expected.
• Must be based in, or willing to relocate to, Austin or Los Angeles.

Nice to have

• Prior experience as a software, computer vision, or data engineer.
• Experience at a sports data or sports technology company.
• Experience with connected devices and sensors.
• Hands-on data analysis skills with SQL and Python.

Culture & Benefits

• Full-time position in the Product department, reporting to the VP of Product.
• Collaborates closely with the computer vision team, Director of Engineering, hardware leadership, and design.
• Success is measured by on-time product delivery, field accuracy and reliability, feature adoption, and cross-functional milestone execution.