Apple

Physical Design Engineer, Machine Learning

Apple
US San Jose, CA, US
Onsite 2026-06-27
Announced salary
$181,100 - $318,400
Low
$116K
Median
$153K
High
$202K
Market in San Jose · BLS OEWS 2025
Estimated net pay
$10,211 - $16,775
/month · 32% withheld
after tax & contributions · Single, no dependents

Job description

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 are 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 will be directly involved in our physical design machine learning efforts, collaborating right alongside our internal multi\-functional teams, and using your expertise in machine learning and physical design 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. **Description** As a member of the physical design machine learning architecture team, 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 RTL design, 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

← See all AI / ML Engineer · San Jose