Machine Learning Engineer

Golf Daddy • Full-time • California, United States, US • 2w ago

About Our Company:

Daddy Sports is committed to making sports simulation widely accessible. The future of sport is practiced and played at-home or in specialized training facilities. We’re making simulators affordable and accessible starting with Golf. We built a $99 golf simulator that is disrupting an industry where the average cost of a simulator is $5000. On all fronts we’ve received tons of recognition, but we’re most proud of our community of over 200,000 supporters on TikTok, Instagram, and YouTube. We started 2 years ago and we’re very early on in our journey, join us today as we blast through an otherwise slow industry and be part of this sports revolution where we turn every sport into an every day option.

Check us out at Golfdaddy.com or in hundreds of stores across the country. (Dicks sporting goods, Golf Galaxy, and more)

We are looking for an experienced Machine Learning Engineer to join us

What you’ll do:

Build the latest and greatest machine learning for sports simulation & improvement
Build compute intensive computer vision models
Collaborate on real world scrappy and innovative data collection strategies
Solve real world problems with machine learning that democratize sports play & practice.

What you’ll need:

5+ Software Engineering experience in Machine Learning or Computer Vision
3+ AWS experience
Extensive understanding of tabular or "traditional" machine learning experience
Ability to create and modify existing deep learning models
Experience dockerizing/deploying/GPU intensive applications
Model conversion and mobile deployment experience

Culture:

Daddy Sport’s culture is lively and in-person. Team members are in the office 5 days per week, 8am to 5pm at the Irvine, CA headquarters. This requires occasional weekend work and long hours. Most will tell you they’d prefer to be nowhere else. There is unparalleled excitement and energy with the speed at which we’re growing and a catalyst to grow your career with the trajectory we’re on. If you want to join an early startup with 1000% YoY growth this is for you.