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Deep Learning Expert at Applied Materials

Rehovot, Center District, Israel -

Full Time

Start Date

Immediate

Expiry Date

14 Apr, 26

Salary

0.0

Posted On

14 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Deep Learning, AI Methods, Model Monitoring, Computer Vision, Python, PyTorch, Model Deployment, Benchmarking, Performance Tuning, Collaboration, Data Augmentation, Training Strategies, APIs, Documentation, Stakeholder Engagement, Visualizations

Industry

Semiconductor Manufacturing

Description

Invent and advance novel AI methods: propose, prototype, and validate new architectures and training strategies that outperform current solutions. Build high‑quality models and pipelines: design datasets, augmentations, and reproducible training/evaluation workflows optimized for experimentation and rapid iteration. Productize for scale: package models with clean APIs and documentation; integrate into production systems with reliability, performance, and maintainability in mind. Trust & governance: implement monitoring (confidence scoring, out‑of‑distribution detection, drift alerts) and benchmarking to prove impact and sustain quality over time. Explainability & adoption: develop intuitive tools and visualizations to clarify model behavior and accelerate stakeholder and customer buy‑in. Cross‑functional collaboration: partner with software, product, and testing teams to align requirements, gather feedback, and deliver high‑impact releases. M.Sc. or Ph.D in Physics, Mathematics , Computer Science or related field 5-8+ years building and shipping deep learning solutions (vision focus preferred). Strong proficiency in Python and DL frameworks as PyTorch. Proven experience taking models from prototype to production (packaging, deployment, runtime integration). Practical knowledge of model monitoring (confidence/OOD/drift), benchmarking, and performance tuning. Solid foundations in computer vision (e.g., segmentation, registration). Comfort with Linux/GPU development environments and modern IDE/tooling. Clear communication skills; ability to collaborate across software, product, and testing. Track record of publishing, patenting, or open‑sourcing innovative AI work.

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Responsibilities

Invent and advance novel AI methods while building high-quality models and pipelines. Collaborate cross-functionally to integrate models into production systems and ensure their reliability and performance.