Head of ML
Mach9
San Francisco, CA · $275k–$400k a year · Posted June 3, 2026
Just laid off? Start here: a plan for the first weeks
Want recruiters in Data & Analytics to be able to find you?
Roles at this level, like this one at Mach9, are often filled through recruiters.
More in California job market · Technology & Software · Data & Analytics jobs
More roles at Mach9
- Software Engineer - 3D Graphics · San Francisco, CA
- Business Development Representative · San Francisco, CA
- Software Engineer - Test Automation (SDET) · San Francisco, CA
- Business Operations Associate · San Francisco, CA
- ML Engineer, Research · San Francisco, CA
- Community Marketing Manager · San Francisco, CA
Similar jobs
- Sr. Data & AI Application Engineer · Xoriant · San Jose, CA
- Research Scientist - Machine Learning · Extropic · San Francisco, CA
- Senior AI/ML Engineer · Condor Software · San Francisco, CA
- AI Engineer · Intellipro Group · Palo Alto, CA
- Senior Staff Engineer, Machine Learning Engineering ( Agentic AI SW ) · Qualcomm · San Diego, CA
- Sr Engineer, Machine Learning Engineering (ML Apps) · Qualcomm · San Diego, CA
Where San Francisco, CA ranks
Where San Francisco, CA placed in our monthly rankings, month by month. Each month stays online at its own address.
November 2026
- #1Best cities for security jobs316 openings · of 20
- #1Best cities for technology jobs7,178 openings · of 100
- #1Best cities for financial services pay after cost of living$173k · of 33
- #1Best cities for entry-level jobs that want AI skills35% · of 100
- #1Best cities for entry-level jobs that want AI skills in the West Coast35% · of 54
- #1Cities with the most jobs that do not need a four-year degree in the West Coast902 jobs · of 47
Rankings about data & analytics jobs
- Best cities for data and analytics jobs #1 New York (1,713 openings)
- Best cities for data and analytics pay after cost of living #1 Foster ($232k)
- Most requested AI skills in data and analytics jobs #1 Machine learning engineering (17.1%)
- AI tools named most often in data and analytics jobs #1 Databricks (7.6%)
- Employers with the most data and analytics jobs #1 Amazon (711 roles)
Data & Analytics jobs · Top Data & Analytics employers · All rankings
How AI is used in this kind of work
Among computer and information research scientists, AI is already used for a large share of the tasks. Measured exposure for computer and information research scientists: 34% (high).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
Say which you have and which you want to build. We use it to match you to jobs like this one.
About the job
THE ROLE
At Mach9, we're building AI to turn dense LiDAR and image data into design-grade CAD deliverables for civil engineering and surveying. We have one of the richest survey-grade datasets in the world. Our product, Digital Surveyor, automates work that takes surveyors and engineers weeks of manual effort.
We're looking for a Head of Machine Learning to build and grow the organization that turns our data into the automated products of the future in surveying and design. This is a hands-on leadership role: you'll set the technical vision for our strategy, mentor and grow a team of ML engineers and researchers, and own the throughline from hard research problems to shipped product capabilities.
This role is ideal for experienced engineers, team leads, and managers who want to push the frontier of 3D computer vision and perception. You’ll have the opportunity to solve problems that few other teams have the data or the talent to take on. We need you to bring a strong vision of what’s possible with our unique dataset, and then to build a team around you to accomplish that vision.
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.
- Ability 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.