Mixed-Signal IP Machine Learning Engineer
2 days ago
Do you love creating elegant solutions to highly complex challenges? Do you intrinsically see the importance in every detail? As part of our Silicon Technologies group, you’ll help design and manufacture our next-generation, high-performance, power-efficient processor, system-on-chip (SoC). You’ll ensure Apple products and services can seamlessly and efficiently handle the tasks that make them beloved by millions. Joining this group means you’ll be responsible for crafting and building the technology that fuels Apple’s devices. Together, you and your team will enable our customers to do all the things they love with their devices. We are seeking a versatile and forward-thinking engineer to join our dynamic team. As a member of our group, you will play a crucial role in the development and implementation of methodologies and solutions with a significant impact on upcoming products, delighting and inspiring millions of Apple customers daily. Your expertise in machine learning will be instrumental in optimizing Power, Performance, Area, and Robustness (PPAR) in our mixed-signal IP development. You will collaborate closely with our internal multi-functional teams to achieve these goals.
Description
As a member of the mixed-signal design team, you will be part of a dynamic team that is building the most efficient silicons on the planet, powering the next generation of Apple products. Your responsibilities will include:
- Develop machine learning models and systems to optimize the Power, Performance, Area, and Robustness (PPAR) of mixed-signal IPs.
- Explore and evaluate various machine learning algorithms to identify the most suitable approaches for specific problems.
- Collaborate closely with firmware, system architecture, and validation teams in a highly engaging and rewarding environment.
- Stay up-to-date with the latest advancements in machine learning and related fields to continually improve our methodologies.
Minimum Qualifications
- Bachelors in Machine Learning, or Computer Science/Electrical Engineering with a focus on machine learning with 3+ years of relevant experience.
Key Qualifications
Preferred Qualifications
- Proven track record of successfully delivering machine learning projects or applications.
- Strong understanding of a wide range of machine learning algorithms, including logistic regression, deep neural networks, and reinforcement learning.
- Solid math background with knowledge of algorithms and data structures.
- Understanding of VLSI fundamentals is a plus.
- Knowledge of signal processing is a plus.
- Strong communication and collaboration skills, with the ability to work effectively in cross-functional teams.
Education & Experience
Additional Requirements
- 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 $143,100 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.
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.
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