Apple Inc.
Machine Learning Research Engineer
Apple Inc., Cupertino, California, United States, 95014
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.Description
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. Your responsibilities will include:Research various components of a DL-based approach to a video processing problem: invent models, design appropriate datasets and pipelines to train them, prototype new architectures to improve performance, study existing literature, and so on.Collaborate closely with team members to optimize the efficiency of the models and deploy them on particular hardware architectures.Work with cross-functional teams to achieve quality and computational requirements towards shipping the technology.Communicate: demonstrate the technology, present to leadership, discuss progress with colleagues, and so on.Minimum Qualifications
Expert knowledge in ML and specifically deep learning: principles, model prototyping and architecture design, training procedures, visualization and debugging methodology, objective function design, and so on.Proven track record of success in deep learning, with publications in top ML/CV venues.Strong familiarity with the latest ML and CV innovations.Excellent software skills in common ML tools such as Python, PyTorch or TensorFlow.Preferred Qualifications
5+ years of hands-on experience in ML research.ML experience in industry.Experience with one of the following: generative modeling, optical flow, perceptual quality, ML for video or data compression.Experience in C/C++; experience implementing custom ops in CUDA.Experience in designing practical ML implementations.Excellent written and oral communication skills.
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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. Your responsibilities will include:Research various components of a DL-based approach to a video processing problem: invent models, design appropriate datasets and pipelines to train them, prototype new architectures to improve performance, study existing literature, and so on.Collaborate closely with team members to optimize the efficiency of the models and deploy them on particular hardware architectures.Work with cross-functional teams to achieve quality and computational requirements towards shipping the technology.Communicate: demonstrate the technology, present to leadership, discuss progress with colleagues, and so on.Minimum Qualifications
Expert knowledge in ML and specifically deep learning: principles, model prototyping and architecture design, training procedures, visualization and debugging methodology, objective function design, and so on.Proven track record of success in deep learning, with publications in top ML/CV venues.Strong familiarity with the latest ML and CV innovations.Excellent software skills in common ML tools such as Python, PyTorch or TensorFlow.Preferred Qualifications
5+ years of hands-on experience in ML research.ML experience in industry.Experience with one of the following: generative modeling, optical flow, perceptual quality, ML for video or data compression.Experience in C/C++; experience implementing custom ops in CUDA.Experience in designing practical ML implementations.Excellent written and oral communication skills.
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