AIML - Machine Learning Researcher, MLR
Company
Apple
Location
Cupertino, CA
Type
Full Time
Job Description
Summary
Posted: Oct 21, 2024
Weekly Hours: 40
Role Number:200574340
Play a part in building the next revolution of machine learning technology. We're looking for passionate mid-level and junior researchers to work on ambitious curiosity driven long-term research projects that will impact the future of Apple, and our products. In this role, you'll have the opportunity to work on innovative foundational research, with focus on Multimodal LLMs and AI Agents. As a member of the team, you will be inspired by a diversity of challenging problems, collaborate with world-class machine learning engineers and researchers to impact the future of Apple products, and publish some of your results in high-quality scientific venues.
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Description
You will propose and co-develop innovative research in the areas of Multimodal LLMs and AI Agents, execute it through implementation and experimentation in collaboration with other researchers and engineers. The research questions revolve around modeling and data decisions that enable strong reasoning and planning capabilities in Multimodal LLMs in particular and Foundation Models in general; techniques and methods of enabling interactive and embodied applications of such models towards AI Agents. Work will involve hands-on rapid prototyping of ideas and use of scalable distributed compute. You will work closely with both researchers but also potentially product partners, resulting in publications as well as prototypes for internal product efforts.
Minimum Qualifications
- PhD, MS or equivalent in Computer Science, Engineering, or equivalent; strong mathematical skills in linear algebra and statistics.
- Demonstrated expertise in Machine Learning or Computer Vision;
- Publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, CoRL, etc).
- Hands-on experience working with deep learning toolkits such as Jax or PyTorch/
- Ability to formulate a research problem, design, experiment, implement and communicate solutions.
Preferred Qualifications
- Work in Foundational Models or Reinforcement Learning.
- Experience with Scalable ML Systems and Frameworks.
- Strong passion for systems-based and mission-driven research with focus on execution and velocity.
- Ability to work in a diverse collaborative environment as part of larger projects.
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 $175,800 and $264,200, 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.
More
- 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.
Date Posted
12/24/2024
Views
0
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