Machine Learning Scientist

Machine Learning Scientist (Direct Hire – Onsite in Irvine, CA) Location: Irvine, CA (Onsite / Hybrid, Monday–Friday, First Shift) or Out of area candidates that fit the qualifications may be considered, for relocation or remote employment with periodic travel to Irvine, CA office. Employment Type: Direct Hire Compensation: DOE (Depending on Experience) Start Date: ASAP Benefits: Medical, Paid Vacation, Paid Holidays, Stock Options We are currently recruiting for a Machine Learning Scientist for a direct-hire role with one of our clients, a technology company based in Irvine, CA. This is not a contract role. Position Overview The Machine Learning Scientist will join a specialized ML team to design, develop, and test advanced deep learning algorithms focused on steganography and media watermarking across digital media formats (images, video, audio, etc.). You will also work closely with engineering teams to deploy these models into production environments, including mobile and cloud platforms. Key Responsibilities Research, design, and implement state-of-the-art deep learning–based steganography algorithms. Collaborate with engineering teams to integrate and deploy ML models to customer-facing platforms. Benchmark and evaluate new models against legacy approaches to ensure quality and accuracy. Prepare clear technical documentation, reports, and presentations to communicate findings to internal teams. Required Qualifications Expert-level experience with PyTorch and training/testing deep neural networks. Experience in dataset collection and curation for deep learning. Strong communication, collaboration, and organizational skills. Preferred Qualifications Knowledge of steganography and digital watermarking techniques. Familiarity with image, video, and audio compression algorithms . Publication history in major ML/CV conferences (CVPR, ICCV, NeurIPS, etc.). Experience deploying ML models to mobile, desktop, or cloud-based customer platforms. Key Concepts (for clarity) Watermarking Embedding identifiable information into digital media (visible or invisible) to prove ownership, track use, or secure content. Steganography Hiding information within media in a way that is undetectable to the human eye or ear. Often used for secure communication or embedding machine-readable signatures. Media Provenance Verifying the origin and authenticity of digital content to ensure it hasn’t been altered—important for combating deepfakes and unauthorized edits. Equal Opportunity Employer Intratek Computer, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, ancestry, national origin, sex, sexual orientation, age, disability, marital status, domestic partner status, or medical condition. Veterans Preference We proudly provide preference to returning war veterans in recognition of their service and skills. #J-18808-Ljbffr Intratek Computer, Inc.