Senior Algorithm Developer – Deep Learning

KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem. Virtually every electronic device in the world is produced using our technologies. No laptop, smartphone, wearable device, voice-controlled gadget, flexible screen, VR device or smart car would have made it into your hands without us. KLA invents systems and solutions for the manufacturing of wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays. The innovative ideas and devices that are advancing humanity all begin with inspiration, research and development. KLA focuses more than average on innovation and we invest 15% of sales back into R&D. Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the world’s leading technology providers to accelerate the delivery of tomorrow’s electronic devices. Life here is exciting and our teams thrive on tackling really hard problems. There is never a dull moment with us.

Job Description/Preferred Qualifications

About the Role

We are looking for a Senior Algorithm Developer to join the AOI (Automatic Optical Inspection) team, working on the EcoNet product.

In this role, you will develop and deploy deep learning–based algorithms that operate as part of a complex, multi‑disciplinary inspection system, combining algorithms, software, system architecture, data, and field constraints.

Beyond strong algorithmic expertise, this position requires broad technical understanding and the ability to work across disciplines to turn advanced AI research into reliable, scalable, customer‑facing solutions.

For the right candidate, this role may also include technical leadership and team ownership.

Key Responsibilities

• Design, develop, and optimize deep learning algorithms for AOI image analysis and inspection use cases
• Conduct applied research, translating state‑of‑the‑art DL methods into robust production solutions
• Take end‑to‑end ownership of algorithms: data analysis, model design, training, evaluation, optimization, and deployment
• Work with large-scale, real‑world data and continuously improve performance, robustness, and scalability
• Collaborate closely with software engineers, system architects, product, applications, and field teams
• Understand and account for system‑level constraints such as throughput, latency, deployment environment, and hardware
• Analyze failures, define KPIs, and drive continuous improvement based on production and field data
• (Optional / Growth Path) Provide technical leadership, mentor team members, and help shape the EcoNet algorithm roadmap

• M.Sc. or higher in Computer Science, Electrical Engineering, Mathematics, Physics, or a related field
• At least 4 years of hands‑on experience in deep learning algorithm development
• Strong background in deep learning theory and practice (e.g., CNNs, transformers, representation learning, optimization)
• Extensive Python experience, including modern DL frameworks (e.g., PyTorch, TensorFlow)
• Proven ability to work on complex, multi‑disciplinary systems, beyond standalone research environments
• Proven experience leading algorithm development efforts, driving technical decisions, and mentoring engineers in a multidisciplinary environment.
• Strong analytical skills and experience working with large, noisy, real‑world datasets
• Ability to translate research ideas into production‑quality, maintainable code

• Work on advanced AI technology that directly impacts customer inspection systems
• A role that combines deep algorithmic challenges with real system and product influence
• Strong cross‑disciplinary collaboration within the AOI organization
• High ownership, autonomy, and a clear path toward technical leadership
• A dynamic environment dealing with real‑world constraints, scale, and complexity

Advantages

• Experience developing production-grade DL systems end‑to‑end
• Experience with C++, especially for performance‑critical components
• Background in computer vision, image processing, or signal processing
• Experience working with distributed systems, inference services, or large‑scale deployment pipelines
• Demonstrated ability to lead technically, mentor others, or grow into a team lead role
• Exposure to industrial systems, high‑throughput pipelines, or customer‑facing products

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