AIML - ML Research Engineer, Forecasting and Optionality

Apple
Cupertino, CA
13 days ago
Apple
Apple
apple.com

Job Description

Summary

Posted: Mar 19, 2024

Weekly Hours: 40

Role Number:200543212

We are a group of innovative researchers and engineers at the forefront of using deep learning to revolutionize high-impact business problems such as Holistic Demand Forecasting, AI-Generated Optionality on sales strategies, supply-demand planning, and financial optimization. As part of our team, you will play a pivotal role in redefining Apple’s product lifecycle, Finance, Sales and Operations through groundbreaking research in deep learning. This role also presents outstanding opportunities to innovate in multi-modal learning, reinforcement learning, sequential models, causal inference modeling, and explainable ML. By collaborating with world-class domain experts from Finance, Sales, Operations as well as top-notch Economists, Engineers and Analysts, our team makes meaningful improvements to the core of Apple's business. Does this sounds exciting? Come join us!

Key Qualifications
  • Demonstrated expertise in deep learning with a proven publication record in reputable conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, KDD, ACL, ICASSP, InterSpeech, or a track record in applying deep learning techniques to real-world problems
  • Proficient programming skills in Python and hands-on experience with at least one of the primary deep learning toolkits, such as JAX, PyTorch, or Tensorflow
  • In-depth experience in relevant areas such as Multi-modal Learning, Reinforcement Learning, Foundation Models (e.g., LLMs), Forecasting, Knowledge Distillation, and Explainable ML, etc.
  • Strong business intuition, adaptive demeanor, and courage to improve established business processes

Description

Your contributions will have direct monetary impact on Apple’s business by translating pioneering deep learning models into explainable and tangible business solutions. We collaborate with outstanding engineers and researches to solve some of the most ambitious problems: AI-Generated Financial Optionality, Foundation Models for demand forecasting, Reinforcement Learning with knowledge distillation, and Explainable Deep Learning.

Education & Experience

Ph.D. experience in Computer Science, Machine Learning, Mathematics or an equivalent field, or 5+ years of industrial experience in the Deep Learning space

Additional Requirements

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 $170,700.00 and $256,500.00, 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.

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