Machine Learning Video Research Engineer
Apple
12 days ago
On-site
Cupertino, California, United States
Video is at the core of nearly all Apple products, and as an engineer on our team, you will research practical ML algorithms and build with us the next generation of video technology. We are looking for a highly ambitious individual, who will flourish working on technically meaningful problems at the frontier of deep learning and compression research. Your work will redefine the video experience for billions of users.
In this role you will work together with colleagues to develop ML-based video approaches for current and future Apple products. This position requires a highly self-directed individual, who is comfortable working at the cutting edge of research. Strong and analytical skills will be critical towards solving challenging problems in uncharted technical territories.
Research various components of a Deep-Learning based approach to image/video processing problems: invent models, design appropriate datasets and pipelines to train them, prototype new architectures to improve performance, study existing literature, and so on\\nCollaborate closely with team members to optimize the efficiency of the models and deploy them on particular hardware architectures\\nWork with cross-functional teams to achieve quality and computational requirements towards shipping the technology\\nCommunicate: demonstrate the technology, present to leadership, discuss progress with colleagues, and so on
BS and a minimum of 3 years relevant industry experience\\n3+ years of hands-on experience in ML research, which can include Ph.D. work\\nProven track record of success in deep learning, with publications in top ML/CV venues\\nFamiliarity with the latest ML and CV innovations, including GenAI modeling techniques\\nSoftware skills in common ML tools such as PyTorch or TensorFlow\\nKnowledge of ML and specifically deep learning: principles, model prototyping and architecture design, training procedures, visualization and debugging methodology, objective function design, and so on
Ph.D. or Master’s degree in Computer Science, Electrical Engineering, or closely related fields\\nExperience implementing custom ops in CUDA\\nExperience in designing practical ML implementations and having ML experience in industry\\nExperience with generative modeling, optical flow, perceptual quality, ML for video or data compression\\nExcellent written and oral communication skills
In this role you will work together with colleagues to develop ML-based video approaches for current and future Apple products. This position requires a highly self-directed individual, who is comfortable working at the cutting edge of research. Strong and analytical skills will be critical towards solving challenging problems in uncharted technical territories.
Research various components of a Deep-Learning based approach to image/video processing problems: invent models, design appropriate datasets and pipelines to train them, prototype new architectures to improve performance, study existing literature, and so on\\nCollaborate closely with team members to optimize the efficiency of the models and deploy them on particular hardware architectures\\nWork with cross-functional teams to achieve quality and computational requirements towards shipping the technology\\nCommunicate: demonstrate the technology, present to leadership, discuss progress with colleagues, and so on
BS and a minimum of 3 years relevant industry experience\\n3+ years of hands-on experience in ML research, which can include Ph.D. work\\nProven track record of success in deep learning, with publications in top ML/CV venues\\nFamiliarity with the latest ML and CV innovations, including GenAI modeling techniques\\nSoftware skills in common ML tools such as PyTorch or TensorFlow\\nKnowledge of ML and specifically deep learning: principles, model prototyping and architecture design, training procedures, visualization and debugging methodology, objective function design, and so on
Ph.D. or Master’s degree in Computer Science, Electrical Engineering, or closely related fields\\nExperience implementing custom ops in CUDA\\nExperience in designing practical ML implementations and having ML experience in industry\\nExperience with generative modeling, optical flow, perceptual quality, ML for video or data compression\\nExcellent written and oral communication skills