Head of Machine Learning & Computer Vision

Bobyard•San Francisco, CA

1d•Onsite

About The Position

Bobyard solves complex computer vision problems to automate takeoffs for contractors, saving dozens of hours per project. This requires building sophisticated model systems that deliver performance at or above human-level accuracy. We’ve built a high-performing computer vision team and are tackling some of the most challenging problems in applied CV. We’re looking for a leader who can help set technical direction, ensure the team is consistently focused on the highest-impact work, and push execution speed and quality. This role will also play a key part in growing the team — maintaining a high hiring bar and developing world-class engineers. The expectation is that the technical standard for this role is as high as our strongest individual contributors. This is a full-time & in-person role in SF. Learning rate and dedication are vital factors. If you can prove that you can execute on the products our customers are waiting for at the speed and quality the market demands (or if you can prove that you will acquire the ability to do so fast enough), we would love to work with you.

Requirements

Strong background in computer vision and deep learning
Experience shipping ML models into real production systems
Comfortable working with messy, real-world data
Research-minded but execution-focused
High ownership mindset — you don’t wait to be told what to fix
Fast learner who can navigate unfamiliar problem spaces
Passion for solving hard, real problems that matter to customers
Strong work ethic — this is a startup, not a cushy big-tech role
Have led a world class CV/ML team before

Responsibilities

Develop and train CV models
Design end-to-end pipelines for data ingestion, training, evaluation, and inference
Scale infrastructure for large training and inference volume while minimizing costs
Entire reliably of systems in production
Improve model accuracy, robustness, and performance at scale
Work closely with fullstack and product to integrate models into production
Analyze real customer data to identify failure modes and opportunities
Stay current with relevant research and apply it pragmatically
Lead technical strategy and direction for the ML team.
Manage and grow ML experts in the team, providing technical guidance, performance feedback, and career development, and acting as hiring manager.