Head of ML

Responsibilities

• Define and drive a coherent vision for how Mach9 can leverage our data advantage to build the best automation products across surveying and design.
• Translate your vision into a technical roadmap, execute strongly, and bring our products to the next level.
• You’ll need to identify which challenges are worth solving, and then which models are ready to ship.
• Build and grow our ML team: hiring, onboarding, structuring the team as it scales, and shaping the split between research and engineering as our organization matures.
• Mentor ML engineers and researchers, providing technical direction, career growth, and guidance to raise the level of the whole team.
• Stay technically hands-on: review designs and code and weigh in on architecture and modeling decisions, so that you stay credible and connected to the team and problems.
• Partner with product and engineering leadership to align Mach9’s investment into research with our product strategy and customer needs.

Requirements

• Experience leading and growing teams — hiring and mentoring ML engineers and researchers.
• 5+ years of work experience in machine learning, with a track record of shipping ML models or systems to production.
• Strong technical depth in machine learning and computer vision, and an ability to set technical direction and to earn the trust of a strong technical team.
• Able to develop technical roadmaps and execute on them.
• Strong communication skills, with the ability to operate across research and engineering.
• Proficient with Python and PyTorch. You must be comfortable engaging deeply with our technical work.

Bonus Qualifications

• Background in machine learning for 3D perception — point cloud understanding, 3D detection/segmentation, geometric deep learning, or related areas.
• Experience with CAD AI, design automation, or applying ML to generate structured/geometric output, rather than just classification or detection.
• Experience scaling an ML organization through a growth phase — defining team structure and hiring strategy.
• Background in domains that work with similar data to Mach9 — remote sensing, geomatics, autonomous driving, or robotics.
• Experience leveraging large unstructured datasets, especially reality-capture datasets, to build data-driven products and flywheels.