深圳中科飞测科技股份有限公司Based in Singapore or Shenzhen，China Algorithm Architect / Lead Algorithm Engineer – Semiconductor Equipment
【Responsibilities】
1.
Architecture & System Design
Lead architecture design for complex algorithm systems, conducting systematic trade-off analysis (detection sensitivity, computational accuracy, real-time performance, cost, and schedule)
Design full-stack algorithm architecture from low-level signal/image processing to high-level AI/ML model inference, ensuring seamless interfaces across layers
Lead algorithm architecture reviews, technical decision-making, and risk assessment; establish error budgets and performance analysis
2.
Development & Implementation
Design, code, and debug high-performance algorithms across image processing, computer vision, machine learning, physical modeling, and numerical optimization
Develop advanced image processing and deep learning algorithms for defect detection and classification, balancing complexity with computational efficiency
Develop algorithm solutions using C/C++, Python, and MATLAB; write efficient, robust code following best practices
Design and implement machine learning/deep learning algorithms for defect detection, classification, and image analysis
Optimize algorithm performance using GPU programming frameworks (CUDA, TensorFlow, PyTorch) for large-scale data processing and real-time inference
Develop and deploy deep learning and optimization algorithms to accelerate learning cycles in semiconductor equipment process workflows
4.
Management & System Integration
Manage full algorithm lifecycle: proof-of-concept, production software design, performance characterization, documentation, and user support
Collaborate with cross-functional teams (software, systems, physics, applications) to integrate algorithms into large-scale systems
Lead problem diagnosis and root cause analysis; design effective test methods for validation
5.
Leadership & Mentoring
Provide hands-on technical leadership, guiding a technical team of 5-10 engineers
Lead design reviews, code reviews, and algorithm performance evaluations; drive structured problem-solving methodologies
【Requirements】
1.
Education & Work Experience
Master's or Ph.D. in Computer Science, Electrical Engineering, Mathematics, Physics, Optics, Microelectronics, or related fields
8+ years of algorithm development experience in semiconductor equipment or high-end industrial systems
5+ years of algorithm development and object-oriented programming experience, with algorithm system architecture design capability
3+ years of technical team management or project leadership experience (semiconductor equipment industry preferred)
2.
Strong theoretical foundation and practical experience in computer vision, machine learning, and deep learning algorithms
Proficiency in C/C++/Python/MATLAB, with algorithm design and software development/debugging skills
Mastery of algorithm performance optimization techniques (CUDA, parallel computing, distributed computing)
Physical modeling and simulation capabilities (optics, electron optics, etc.)
Deep understanding of algorithm development lifecycle, with proven ability to transition from prototype to production
Strong background in at least one of the following: image processing/computer vision, computational geometry/nonlinear optimization, physical modeling/HPC, optics/microelectronics processing
3.
Full lifecycle algorithm product development experience
Excellent cross-functional collaboration and communication skills
Structured problem-solving ability with data-driven decision making
Self-motivated with strong initiative and intellectual curiosity; ability to work independently
Ability to thrive in a fast-paced, customer-driven environment
4.
Algorithm development experience for semiconductor inspection, metrology, or lithography equipment
Experience with electron-beam image processing, SEM image analysis, or electron optical system algorithms
Algorithm development experience in computational lithography (OPC)
High-precision metrology algorithm experience (CD-SEM, OCD, overlay metrology)
Familiarity with semiconductor data formats (GDS, OASIS, KLARF, etc.)
Production-level experience with deep learning frameworks (TensorFlow, PyTorch)
Publications in top conferences/journals (CVPR, ICCV, NeurIPS, etc.)
Experience working with multi-site, cross-regional teams
Interested in this role?