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Apple Multimodal Generative Modeling Research Engineer - SIML ISE United States, Washington, Seattle 264461898
25.03.2025
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Description
We are looking for a candidate with proven track record of leading applied ML research. Responsibilities in this role will include creating multimodal Generative AI models that can deliver high quality and enable new capabilities in support of production focussed user experiences. You will do this through distributed training of large scale models involving image/video/audio and research optimizations for deploying efficient models on device. Ensuring high quality in real world use, mitigating bias and preserving privacy are all core tenets. You will be interacting closely and cross-functionally with other ML researchers, software engineers, hardware & design teams.
Minimum Qualifications
- M.S. or PhD in Computer Science or a related field such as Electrical Engineering, Robotics, Statistics, Applied Mathematics, or equivalent experience.
- Hands on experience training or adapting image / video / audio generation models (eg: SDXL, Flux, etc) for downstream tasks
- Proficiency in ML frameworks e.g., PyTorch, Tensorflow
- Strong programming skills in Python / other high level languages
Preferred Qualifications
- Familiarity with distributed training
- Strong programming skills in C/C++/ObjC
Pay & Benefits
- At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $166,600 and $296,300, and your base pay will depend on your skills, qualifications, experience, and location.Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.
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