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 SoC Physical Design Engineer, Methodology and Machine Learning - Cupertino, California, United States

Job information
Posted by: Apple 
Hiring entity type: Retail 
Work authorization: Not Specified for United States
Position type: Direct Hire, Full-Time 
Compensation: ******
Benefits: See below
Relocation: Not specified 
Position functions: Computers - Software Engineer
Travel: Unspecified 
Accept candidates: from anywhere 
Languages: English - Fluent
Minimum education: See below 
Minimum years experience: See below 
Resumes accepted in: English
Cover letter: No cover letter requested
Job code: 200183548 / Latpro-3748473 
Date posted: Jul-29-2020
State, Zip: California, 95014


SoC Physical Design Engineer, Methodology and Machine Learning

Santa Clara Valley (Cupertino) , California , United States



Posted: Jul 28, 2020

Role Number: 200183548

At Apple we believe our products begin with our people. By hiring a diverse team, we drive creative thought. By giving that team everything they need, we drive innovation. By hiring incredible engineers, we drive precision. And through our collaborative process, we build memorable experiences for our customers. These elements come together to make Apple an amazing environment for motivated people to do the greatest work of their lives. You will become part of a hands-on development team that sets the standard in cultivating excellence, creativity and innovation. Come help us design the next generation of revolutionary Apple products. We're looking for a forward-thinking and unusually talented engineer. As a member of our dynamic group, you will have the rare and rewarding opportunity to craft and implement methodologies and solutions with a high impact on upcoming products that will delight and inspire millions of Apple's customers every single day. In this role, you'll be directly involved in our physical design methodology efforts, collaborating right alongside our internal multi-functional teams, and using your expertise in machine learning to ensure that our SOCs achieve the optimal Power, Performance, and Area (PPA). We account for every nano watt, every nano meter, and every pico second.

Key Qualifications

  • Strong intellectual curiosity
  • Solid math background and understanding of algorithms and data structures
  • Excellent communication and organization skills
  • Practical experience and knowledge in various machine learning algorithms, from linear and logistic regression to deep neural networks and reinforcement learning
  • Excellent programming skills in Python and C++
  • 3+ years of physical design experience, including synthesis, place and route, extraction, STA and physical verification
  • Solid understanding of circuit design is a plus
  • Experience with flow development for a large number of users on a tight schedule is a plus.


As a Physical Design Methodology and Machine Learning engineer you will be part of a dynamic team that is building the most efficient application processors on the planet, powering the next generation of Apple products. You will use your experience in physical design and machine learning to solve very hard and unique problems. Your work will directly impact vast areas of the flow including logic synthesis, floor planning, power/clock distribution, place and route, timing/noise analysis, power/thermal analysis, voltage drop analysis, design for manufacturing/yield, and beyond. As part of your work, you will collaborate cross functionally with design, power, post silicon, CAD, software and machine learning teams.

Education & Experience

Minimum Bachelors Degree in EECS.


See job description


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