Machine Learning Engineer

Steg.AI; Irvine (CA); On-site; USD 120,000 - 190,000; Full time

Job summary

Steg.AI in Irvine, CA is seeking a Machine Learning Engineer to productionize steganography models, build inference pipelines, and deploy capabilities on desktop and cloud platforms. You will bridge research and customer-facing products, turning cutting-edge ideas into reliable software.

Join a small team of PhDs focusing on watermarking, media provenance, and scalable ML systems. Onsite collaboration and full-time commitment are expected.

Qualifications

• Proficient in PyTorch and ONNX export.
• Experience deploying deep learning models to the cloud.
• Strong Python and C/C++ programming skills.
• Excellent cross-team communication and collaboration.

Responsibilities

• productionize novel steganography models
• build inference pipelines
• integrate models into cloud platforms
• benchmark performance
• turn research into maintainable production code.

Skills

PyTorch

ONNX export

cloud deployment

Python

C/C++

cross-team communication

Job description

Steg.AI | Machine Learning Engineer | Irvine, CA (Onsite) | Full Time

Steg.AI develops AI-powered watermarking technology to protect and authenticate digital media. Our invisible watermarks are imperceptible to humans but robustly detectable by our proprietary models. Founded in 2019, we're an NSF- and investor-backed startup in Orange County, CA, 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. You'll take state-of-the-art steganography models and own their journey to production - optimizing and deploying them on desktop and cloud platforms, serving as the link between research and customer-facing products.

Responsibilities:

• productionize novel steganography models
• build inference pipelines
• integrate models into cloud platforms
• benchmark performance
• turn research into maintainable production code.

Required:

• PyTorch
• ONNX export
• experience deploying deep learning models to the cloud
• Python and C/C++
• strong cross-team communication.

Bonus:

• background in steganography/watermarking/media provenance
• video/image codecs
• MLOps tooling
• CV/ML publications or open-source contributions.

Contact: [e-mail]