The impact you’ll make

This internship role will focus on Image Segmentation / Image Processing / Computer Vision (CV). The successful candidate will focus on the Model assisted active learning, ML-based label quality scoring, assistive data labeling, and data management tool for image segmentation. Specifically, the intern will be involved in the design and development of iterative and assistive data labeling tool backed by Lam’s most powerful image segmentation, Foundation Models.

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Who we’re looking for

Post-Graduates (Final Year Students - Master / PhD Program) with strong passion and understanding of Deep Learning (DL), Machine Learning (ML), and Computer Vision (CV).

Good knowledge and understanding in machine learning, deep learning, image processing / computer vision. Knowledge on Image segmentation is a MUST.
Strong proficiency in Python programming and debugging, associated libraries like OpenCV, PyTorch, PyQt, GUI, NumPy, Scikit-learn, etc.
Self-driven personality with the team-work mindset and self-reliant working style.
Previous relevant works in image segmentation, UNET, SAM, is a big plus.

This is purely a data science (DL for computer vision) work and hence, NO knowledge on semiconductor, hardware, etc. is required.

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About the company

Lam Research

Company overview

Lam Research builds semiconductor manufacturing equipment, with a focus on wafer fabrication tools used in processes like etch and deposition. Lam Research also sells software, upgrades, spares, and services that support chipmakers over the life of installed equipment. The company serves major semiconductor manufacturers worldwide and operates across R&D, manufacturing, and field service functions. Lam Research is a public company (Nasdaq: LRCX).

Locations and presence

Lam Research is headquartered in Fremont, California and operates a large U.S. footprint including Oregon (Tualatin, Sherwood, Hillsboro) plus other sites, alongside a broad global network of offices and manufacturing locations. Lam Research job postings describe hybrid models such as “On-site Flex” (3+ days on-site) and “Virtual Flex” for roles that allow more remote work, with expectations set role-by-role.

Palpable Score

75.1

/ 100

Lam Research is an accessible early-career employer for engineers and STEM grads because Lam Research runs internships, co-ops, and a named Graduates Program, backed by structured onboarding and buddy support. Lam Research also has visible pay and benefits signals in job postings and public perks, plus a clear hybrid-work model vocabulary that helps candidates understand what “hybrid” means in practice. The score is capped by limited public detail on interview stages for early-career roles and a lack of published early-career outcomes metrics like conversion, retention, and promotion rates.

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