Software Engineer - ML Performance / HPC

Posted:
7/10/2024, 6:58:41 AM

Location(s):
Texas, United States ⋅ Dallas, Texas, United States

Experience Level(s):
Junior

Field(s):
AI & Machine Learning ⋅ Software Engineering

Workplace Type:
On-site

54,000 new photos are taken every second, and 600 hours of video are uploaded every minute. At Topaz Labs, we help over 1 million paying customers (including teams at Apple, Netflix, and NASA) maximize the visual quality of over 1 billion of these photos and videos. 

About us

Topaz Labs is a full-stack AI company that develops, trains, and deploys generative AI models for image and video enhancement. We’re the best in the world at improving image and video quality, and produce several award-winning desktop products that millions of people rely on. 

About the role 

As a Software Engineer - ML Performance, you would report to our Head of AI Engine, and use your expertise to improve performance of our internal AI Engine. Your responsibilities will be to increase app performance, stability, availability of new features and simplify and improve the API of the framework. You will be the technical bridge between our Deep Learning research team and our variety of Production products that rely on our models. You’ll support our research team by helping prepare new & updated models for production and helping with GPU/CPU optimization. You’ll also work with various hardware partners (NVIDIA, AMD, Intel, Apple) to optimize inference on their hardware.

Do you meet most but not 100% of the above? We’d still like to hear from you–we are passionate about developing a diverse team and culture, so please apply if you’re interested! 

This is a unique role for someone interested in making a deep impact at a high-growth tech software company. We offer strong base salary, plus significant ownership that scales with the company's growth. We also offer 100% covered medical/dental/vision for employees, 15 days annual PTO, 5 days of personal time plus holidays, and 401k matching. This is a full-time onsite role in Dallas, TX, and we will ask you to relocate if you're not in the area.