AIML Resident - ML Research - Controllable Generative AI

Summary

Posted: Nov 22, 2024

Role Number:200574846

Imagine what you could do here! At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Combining groundbreaking machine learning research with next-generation hardware, our teams take user experiences to the next level.

Description

Apple's AIML residency is a year-long program inviting experts in various fields to apply their own domain expertise to innovate and build revolutionary ML and AI-based products and experiences. As AI-based solutions spread across fields, the need for domain experts to understand machine learning and apply their expertise in ML setting grows. Residents will have the opportunity to attend ML and AI courses, learn from an Apple mentor closely involved in their program, collaborate with fellow residents, gain hands-on experience working on high-impact projects, publish in premier academic conferences, and partner with Apple teams across hardware, software, and services. Our team is part of the Apple Machine Learning Research (MLR) organization and conducts fundamental research in two areas: (i) controllable generation, aimed at enhancing the controllability and capabilities of multi-modal generative models including 3D, vision, language, audio and motion. This enables techniques such as creating and augmenting virtual worlds with advanced controls, and generating synthetic data for training downstream models; and (ii) efficient machine learning, focusing on optimizing models and algorithms for high performance while minimizing resource usage by improving data efficiency, reducing training time, and lowering inference compute and memory demands. A few recent representative works from the team include: - "Probabilistic Speech-Driven 3D Facial Motion Synthesis: New Benchmarks, Methods, and Applications (https://arxiv.org/abs/2311.18168)", CVPR 2024 - "HUGS: Human Gaussian Splats (https://machinelearning.apple.com/research/hugs)"Pointersect: Neural Rendering with Cloud-Ray Intersection (https://arxiv.org/abs/2304.12390)", CVPR 2023 - "MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training (https://arxiv.org/abs/2311.17049)"Corpus Synthesis for Zero-shot ASR domain Adaptation using Large Language Models (https://arxiv.org/abs/2309.10707)", ICASSP 2024 - "Tic-clip: Continual training of clip models (https://machinelearning.apple.com/research/tic-clip-v2)", ICLR 2024 - "GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models (https://machinelearning.apple.com/research/gsm-symbolic)", arXiv 2024 Play a part in building the next revolution of machine learning technology. Our ML Research team is looking for a hard-working resident to conduct research into multi-modal (vision, 3D, language, audio) generative models along with exploring effective control mechanisms for these models. As a member of our team, you will work on some of the most ambitious technical problems, collaborate with world-class machine learning engineers and researchers, develop new ML solutions that will impact future Apple products, and publish your results in high-quality scientific venues.

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• Proficiency in a programming language such as Python, and/or C++. Candidates should have experience completing a moderate-sized software project
• Proficiency using ML toolkits, e.g., PyTorch, Jax or Tensorflow
• Demonstrated ability to connect and collaborate with others
• Graduate degree or equivalent experience in a STEM field or industry experience in software engineering
• Apple's AIML residency is a one-year program starting in July 2025. Residents must be available to work full-time (40 hours/week) July 14, 2025 - July 10, 2026

• Ideal candidates will also have academic, research, or proven experience in one of the following: Large Language Models / Generative AI, Machine Learning & ML Research, Natural Language Processing/Speech/Conversational AI, Robotics, or Computer vision. Thesis, capstone project, internship, co-op, and/or experience in these fields qualifies
• Strong publication record in top machine learning conferences such as ICML, NeurIPS, CVPR, ICCV is a plus
• We encourage you to submit a cover letter as part of your application explaining: What are your research interests? How do they apply to the specific Residency position you applied to? Why you would like to join the AIML residency program broadly?
• APPLICATION DEADLINE: DECEMBER 16, 2024

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 $135,400 and $204,000, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

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. Learn more about your EEO rights as an applicant.