Software Engineer, AI Inference / HPC

Topazlabs; Dallas (TX); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Full medical/dental/vision coverage

15 days PTO

5 personal days + holidays

401k matching

Job summary

Topaz Labs, a full-stack AI company, is seeking a Software Engineer to support our AI Engine and improve the performance of our internal AI framework. You will bridge the Deep Learning research team with production products, and optimize GPU/CPU paths while preparing models for deployment.

You will collaborate with hardware partners such as NVIDIA, AMD, Intel, and Apple to optimize inference and enhance image processing capabilities. This is a full-time onsite role in Dallas, TX.

Qualifications

• Strong C/C++ expertise and system-level optimization.
• Experience with performance optimization, concurrency, multithreading.
• Experience with image processing/photography algorithms.
• Experience with OpenCV, ffmpeg and GPU programming.
• Experience with video encoding/decoding and file formats.

Responsibilities

• Improve performance of the internal AI Engine and APIs.
• Bridge between DL research and production products.
• Prepare models for production and optimize for GPU/CPU.
• Collaborate with hardware partners (NVIDIA, AMD, Intel, Apple) for inference optimization.

Skills

Performance optimization

APIs for internal development

Image processing algorithms

C/C++ expertise

Professional experience 1+ years

Video encoding/decoding

OpenCV & FFmpeg

GPU programming

Raw image pipeline

ONNX/CoreML/TensorRT

Photography / videography interest

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

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.