AI Jobs

Experience Requirements:

• 3 years of experience/knowledge in device modeling and TCAD simulation

• Understanding of semiconductor device physics

• Knowledge in Synopsys TCAD tools

Other Requirements:

• Willingness to learn new technologies and tools

Responsibilities:

• TCAD simulation

• Setting up Verilog-A & Spectre models, and simulation of these

• Simplification of mathematical device models for faster simulation

• Process engineering to fabricate devices in R&D and volume fabs

Education Requirements:

• BS/MS/PhD in EE, CS, or a related field

Experience Requirements:

• Understanding in computer architecture, digital design, and micro-architecture concepts

• Familiarity with AI/ML algorithms, frameworks, and workloads

• Programming experience in C/C++ and Python

Responsibilities:

• Design and specify core architecture modules

• Partner with the software team to evaluate module performance

• Monitor emerging trends and research in AI workloads

Experience Requirements:

• 5+ years experience

• Extensive knowledge in analog design in theory and hands-on

• At least two successful tape-out

• Experience in chip measurement

Responsibilities:

• Determining the specifications of the analog blocks

• Design & implement ultra-low power analog IC periphery blocks

• Contribute the layout floor-plan

• Post-layout characterization

• Developing the verification scheme for analog blocks

Education Requirements:

• Background in component-level circuit design & general electrical engineering

Experience Requirements:

• Experience with mechanical CAD design

• Experience with Python scripting or Matlab, LabView

Other Requirements:

• Interest in test automation for highly integrated analog circuits

• Base knowledge / interest to re-learn semiconductor device physics

Responsibilities:

• Design mechatronic assemblies for automated test & characterization

• Program automation routines for automated testing

• Design PCBs for test automation

• Design PCBs for prototype systems

Experience Requirements:

• In-depth knowledge of C++

• Hands-on experience in compiler technologies like LLVM

Responsibilities:

• Building/maintaining ML compiling toolchain

• Design & implement various compiler operations

• Collaborate with ML & quantization engineers/researchers

Education Requirements:

• Master’s degree, PhD, or strong engineering skills/understanding of ML tooling

Experience Requirements:

• Fluency in Python and PyTorch

• Understanding of training workflows

• Practical experience with model optimization

• Ability to architect and maintain scalable systems

Other Requirements:

• Collaborative mindset

Responsibilities:

• Design and implement a geo-distributed QAT system

• Build collaborative training and tooling infrastructure

• Translate new quantization methods into engineering components

• Collaborate with researchers

Benefits:

• Equity

Education Requirements:

• PhD or equivalent research experience in machine learning, mathematics, or related field

Experience Requirements:

• Strong understanding of quantization, model optimization, and numerical methods

• Proficiency in Python and PyTorch

Other Requirements:

• Research mindset: curiosity, rigor

Responsibilities:

• Research and develop novel analog-aware quantization methods

• Design mathematically principled matrix-vector multiplication algorithms

• Collaborate with analog hardware engineers to define algorithmic requirements