Mixed-Signal IP Machine Learning Engineer

$143,100 - $264,200/Yr

Apple - Cupertino, CA

Full-time - Mid Level

Cupertino, CA

Computer and Electronic Product Manufacturing

About the position

As a member of the Silicon Technologies group at Apple, you will play a crucial role in designing and manufacturing next-generation, high-performance, power-efficient processors and systems-on-chip (SoC). This position focuses on optimizing Power, Performance, Area, and Robustness (PPAR) in mixed-signal IP development through machine learning methodologies. You will collaborate with multi-functional teams to ensure that Apple products can efficiently handle tasks that delight millions of customers.

Responsibilities

• 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.

Requirements

• Bachelors in Machine Learning, Computer Science, or Electrical Engineering with a focus on machine learning.
• 3+ years of relevant experience in machine learning.

Nice-to-haves

• 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.

Benefits

• Comprehensive medical and dental coverage
• Retirement benefits
• Discounted products and free services
• Reimbursement for certain educational expenses, including tuition
• Discretionary bonuses or commission payments
• Relocation assistance