Applied Computer Vision Engineer

# Machine Learning Engineer**Full Time - In Office - Irvine, CA**## About Steg.AISteg.AI develops AI-powered watermarking technology to protect and authenticate digital media. Our invisible watermarks are designed to be imperceptible to humans while remaining robustly detectable by our proprietary models.Founded in 2019, Steg.AI is an NSF- and investor-backed startup based in Orange County, California, with a team of 6 PhDs in computer vision.We're hiring a Machine Learning Engineer to help push the frontier of AI for watermarking, steganography, and media provenance.## Job DescriptionYou'll take our state-of-the-art steganography models to production, optimizing and deploying them in our SDKs and cloud platform, and extending them to new image and video formats. **You won't train new models, but you'll build scaffolding and features around them to boost performance of our watermarking algorithms.** As part of the Engineering and Research teams, you'll be the link between research and customer-facing products.## Scope of Responsibility* Productionize our models with inference pipelines for our cloud platform and SDKs* Extend watermarking to new file types and codecs* Build image, video, and audio pipelines (decode, color conversion, resampling, re-encode)* Recover watermarks from transformed media using image processing techniques* Benchmark quality and robustness, and track regressions## Required Qualifications* 3+ years of full-time industry experience in computer vision or image/video processing* Python, OpenCV, NumPy, ONNX, ONNX runtime* Traditional 2D/3D computer vision techniques: feature matching, object detection, model estimation, optimization, etc.* Image/signal processing: imaging, compression, color spaces, filtering, resampling, etc.* FFmpeg and video codecs such as H.265 and HEVC## Bonus Qualifications* C/C++, PyTorch, Pillow* Familiarity with steganography, watermarking, or media provenance technologies* MLOps tooling: model registries, CI/CD for ML, and monitoring## To ApplySend your resume/CV to **[email protected]**

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