Physical Implementation Engineer– Machine Learning
Core
Develop and verify ML and Neural Network hardware IP, optimizing Power, Performance, and Area (PPA) for mobile, IoT, and autonomous vehicle applications.
Role type
Senior IC physical implementation engineer (ML hardware)
Builds
Next-generation Arm IP for mobile apps, portable devices, home automation, smart cities, and autonomous vehicles
Domain
Semiconductor hardware design and Machine Learning
Deliverable
production ML models (via careerplan.io/jobs/100918785280-physical-implementation-engineer-machine-learning-at-arm)
Required skills
Digital hardware design, Hardware description languages (VHDL, Verilog, SystemVerilog), Physical implementation flow (RTL, Synthesis, Place & Route, LEC, STA), PPA trade-off analysis, EDA tool suite usage
Preferred skills
Low power build features (clock/power gating, voltage/frequency scaling), Scripting (Python, TCL, Bash, MAKE), RTL simulation and verification, Machine learning/AI fundamentals
Technologies
Synopsys, Cadence, Mentor, Python, TCL, Bash, MAKE
Responsibilities
Identify critical bottlenecks across IP development, Analyze and optimize power for next generation IP, Provide timing, power and area analysis and recommendations, Support partners to achieve best PPA results, Liaise with implementation groups to improve flow alignment, Work with latest technology nodes and EDA tools
