Overview
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 Google, Nvidi
Full job description
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 Google, Nvidia, 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 supporting our AI Engine, 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.
Hands-on experience with performance optimization, e.g. concurrency, multithreading, memory, speed, benchmarking, reliability Experience architecting APIs for internal development Hands-on experience implementing image processing or computational photography algorithms Expert knowledge of C/C++ At least 1+ years of professional working experience in a related field
Experience with video encoding/decoding and file formats Experience with OpenCV, ffmpeg, GPU programming Experience with the raw image camera pipeline and image formats Experience with onnx, coreml, and tensorRT runtime SDKs Interest in photography or videography
Tips for this job
Practical Job and Scholarship guidance. These tips do not replace official rules or create new eligibility requirements.
- Tailor the CV and application to the responsibilities and required skills stated on the official employer page.
- Use concrete evidence of relevant work, projects and measurable results rather than generic claims.
- Confirm location, work authorization, remote restrictions and sponsorship terms before applying.
- Apply through the original employer or official recruitment destination shown on this page.
Verification notes
laptop-ats-crawler v3
Job and Scholarship is the discovery and verification layer. Confirm eligibility, dates, salary/funding and application instructions on the original source before submitting anything.
Topaz Dex (lever) ↗Browse current Job and Scholarship listings from Topaz Dex (lever) →