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Apple AIML - Full Stack ML Engineer LLM Optimization United States, California, Cupertino 68447489
13.06.2024
Description
As a Full Stack ML Engineer on our team, you will leverage your background to:* Design and implement ML-based solutions to improve runtime latency, training time, memory usage, time to first token, and decoding speed for Apple applications* Innovate across the entire end-to-end ML production pipeline, including dataset creation, neural network architecture design, model training, fine-tuning methods, training time optimization, on-device and server side inference* Quickly prototype and iterate to achieve high-quality implementations for pioneering machine learning algorithms* Collaborate with hardware and software teams to integrate research findings into market-ready solutions* Translate theoretical ideas into tangible innovations, demonstrating their industrial applicability
Preferred Qualifications
- Strong ML background
- Proficiency in Programming Languages and Frameworks: Python, C++, PyTorch/TensorFlow/Jax
- Experience with Natural Language Processing(NLP), ML optimization - with a focus on LLMs
- Outstanding communication and technical writing skills, capable of conveying complex concepts clearly and efficiently
- Preferred: notable achievements validated by quality publications in ML optimization, with a focus on LLMs
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 $170,700 and $300,200, 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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