Position OverviewBobyard 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.
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.
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.
Desired Attributes- 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
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.
