• Graduate with a MS, or Ph.D. degree in Computer Science, Computer Engineering, Applied Math, or related field.

• Can work independently, define project goals and scope, and lead your own development effort.

• Strong Python or C++/C programming and software design skills, including debugging, performance analysis, and test design.

• Experience with Deep Learning Frameworks such as PyTorch, TensorFlow, and MXNet

• Experience with model acceleration techniques such as deep learning quantization, model pruning, and model distillation.

Ways to stand out from the crowd:

• Experience with numerical methods

• Knowledge of computer architecture

• Experience with AI compilers

• Experience in model deployment within the autonomous driving industry

• Experience deploying LLMs on edge devices

• You are graduating with a MS, or Ph.D. degree in Computer Science, Computer Engineering, Applied Math, or related field.

• You can work independently, define project goals and scope, and lead your own development effort.

• Strong C++/ C or Python programming and software design skills, including debugging, performance analysis, and test design.

• Strong expertise on one of these directions:

• deep learning quantization

• NN compiler (TVM, MLIR, GLOW, LLVM) experience

• NN model pruning

• Cadence DSP programming

Ways to stand out from the crowd:

• Numerical methods experience

• Knowledge of computer architecture

• Python experience

• Experience with Deep Learning Frameworks such as TensorFlow, PyTorch, and MXNet

• Strong proficiency in compiler development, including experience with LLVM, MLIR, TVM, or similar frameworks.

• Expertise in Machine Learning model execution, optimization, and deployment.

• Strong programming skills in C++, Python, and assembly-level optimizations.

• Knowledge of parallel computing, vectorization, and memory hierarchy optimizations.

• Familiarity with deep learning frameworks (TensorFlow, PyTorch, ONNX).

• Strong analytical skills for performance profiling and debugging.

• Experience in graph optimizations, quantization, and code generation.

Preferred Qualifications

• Knowledge of heterogeneous computing, DSPs, and low-level hardware programming.

• Familiarity with AI model deployment and inference optimization techniques.

• Background in high-performance computing (HPC).

• MS/PhD in Computer Science, Electrical Engineering, or a related field.

• 2+ years of experience in computer vision, machine learning, and deep learning development.

• Proficiency in Python and C++ with hands-on programming skills; familiarity with embedded systems is a plus.

• Experience with one or more of the following areas:

• Deep network development (visual data focus), object detection, tracking, and 3D computer vision (stereo, optical flow, depth estimation).

• Structure from motion, network-based sensor fusion, and mathematical optimization.

• Familiarity with ADAS and autonomous driving technology, particularly in 3D object detection and semantic segmentation.

• Mandarin proficiency is a plus.

• Bachelor’s or Master’s degree in Electrical Engineering, Computer Science, Semiconductor Engineering, or related technical field.

• JD (Juris Doctor) or equivalent legal qualification from a recognized institution.

• 1-3 years of experience in IP law, preferably in the semiconductor or technology industry.

• Admission to a bar association and registration with a patent office (e.g., USPTO, CNIPA, EPO) is preferred.

• Strong knowledge of patent laws, IP litigation, and technology licensing.

• Ability to analyze complex technical and legal issues and provide strategic recommendations.

• Excellent communication and organizational skills.

Bilingual: English/Mandarin Preferred