Job Description/Preferred QualificationsWe are looking for a full-time
Deep Learning Algorithm Engineer who is passionate about pioneering
Deep Learning (DL),
foundation models, and
GenAI for image processing and computer vision applications in the
semiconductor process control business.
Qualified candidates are expected to have a strong background and in-depth experience in deep learning, especially in object detection, segmentation, vision foundation models, and multimodal models. Candidates should also have a deep understanding of relevant theory and hands-on experience grounding DL/GenAI models in real application domains, with strong emphasis on
performance, efficiency, and deployment.
The ideal candidate can work independently across the full deep learning project lifecycle, including conceptualizing, exploring, designing, implementing, optimizing, and deploying models. Responsibilities for this position include, but are not limited to:
- Understand state-of-the-art (SOTA) deep learning and GenAI models.
- Connect SOTA DL modeling approaches to domain problem statements.
- Analyze modeling requirements based on product feature requirements.
- Design deep learning and GenAI models to meet modeling requirements.
- Implement modeling prototypes and perform analysis.
- Perform model training and/or tuning on domain datasets.
- Evaluate and validate model performance against defined metrics.
- Analyze model performance bottlenecks.
- Design and optimize DL model architectures, including new modules, efficient backbones, and model compression techniques (e.g., distillation).
- Optimize DL or GenAI model throughput and cost, including mixed-precision and low-precision inference and training (e.g., FP16, FP8).
- Work and communicate collaboratively with peers.
- Present ideas, concepts, and results in professional technical settings.
Qualifications/Education Desired- Ph.D. in Electrical Engineering, Computer Science, or related quantitative fields.
- Academic or industrial experience applying deep learning or GenAI to real-world problem(s), with impactful results.
- In-depth experience developing and optimizing deep learning, Vision Foundation Models (VFM), or Vision Language Models (VLM) in at least one of the following areas: computer vision, image processing, robotics, NLP, or equivalent, with strong emphasis on efficiency, scalability, and deployment performance.
- Required experience with DL model optimization/distillation for mixed or reduced precision (e.g., FP16, FP8) to improve throughput, latency, and deployment efficiency.
- Experience with GenAI coding tools, vibe coding, or vibe engineering.
- Proficiency in Python and one additional programming language from: C++, Java, Rust, Go.
- Proficiency in at least one deep learning framework (e.g., PyTorch, TensorFlow, JAX, or equivalent).
- Demonstrated deep learning expertise via technical publications in top conferences (e.g., NeurIPS, CVPR, ICML, ICLR, KDD, SIGGRAPH, etc.) and/or industrial patents and/or impactful open-source projects is required.
- Travel required: up to 10%.
- Experience in semiconductor process control is a plus.
Minimum Qualifications- Doctorate (academic) degree with 0 years of related work experience; or Master's degree with 3 years of related work experience.
- Academic or industrial experience applying deep learning or GenAI to real-world problem(s), with impactful results.
- Required experience with DL model optimization/distillation for mixed or reduced precision (e.g., FP16, FP8) to improve throughput, latency, and deployment efficiency.
- Travel required: up to 10%.
Base Pay Range: $136,300.00 - $231,700.00 Annually
Primary Location: USA-CA-Milpitas-KLA
KLA's total rewards package for employees may also include participation in performance incentive programs and eligibility for additional benefits including but not limited to: medical, dental, vision, life, and other voluntary benefits, 401(K) including company matching, employee stock purchase program (ESPP), student debt assistance, tuition reimbursement program, development and career growth opportunities and programs, financial planning benefits, wellness benefits including an employee assistance program (EAP), paid time off and paid company holidays, and family care and bonding leave.
Interns are eligible for some of the benefits listed. Our pay ranges are determined by role, level, and location. The range displayed reflects the pay for this position in the primary location identified in this posting. Actual pay depends on several factors, including state minimum pay wage rates, location, job-related skills, experience, and relevant education level or training. We are committed to complying with all applicable federal and state minimum wage requirements where applicable. If applicable, your recruiter can share more about the specific pay range for your preferred location during the hiring process.
