Algorithm Engineer - Deep Learning (E)

KLA • Milpitas, CA

2d

About The Position

Algorithm Engineers are core to KLA’s technology, while we do not currently have an opening, we are always building our Algorithm Engineering talent community, we are interested in learning about your background. Apply to this posting for Future Opportunities with KLA. We 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 models in a real application domain. The ideal candidate can work independently across the full deep learning project lifecycle, including conceptualizing, exploring, designing, implementing, and deploying.

Requirements

• 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 applying 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.
• 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%.
• 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.
• 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%.

Nice To Haves

• Experience with DL model optimization for reduced precision (e.g., FP8, FP4) is a plus.
• Experience with VFM pretraining or post-training is a plus.
• Experience in semiconductor process control is a plus.

Responsibilities

• 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 new DL modules or components to improve performance.
• Optimize DL or GenAI model throughput and/or cost.
• Perform A/B testing between models on real data.
• Work and communicate collaboratively with peers.
• Present ideas, concepts, and results in professional technical settings.

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree