Director, AI Lab at Lam Research
Fremont, CA
$168,000–$350,000from the description
Jul 1, 2026
Fremont, CA
Jul 21, 2026
What this job asks for AI summary
This is a founding leadership role responsible for building and running a new applied AI lab from scratch, housed within the Office of the CTO. Day-to-day work spans setting the lab's technical direction, hands-on development of AI prototypes and proof-of-concepts, and shepherding successful experiments into production-ready solutions across engineering, manufacturing, and corporate functions. The role also involves hiring and growing a team of AI engineers and researchers, making it best suited to a technically deep leader with a track record of standing up AI innovation programs in complex organizations.
Principal level · San Jose-Sunnyvale-Santa Clara, CA · Full-time
We read this from the posting text with AI. Skim the description below before ruling yourself out.
Why we read it this way (7)
This is a founding Director-level people-management role (building and leading a new AI Lab from scratch, with direct reports including AI engineers, researchers, and technical specialists), making 11-3021 the primary SOC. However, the JD strongly emphasizes hands-on technical work — building prototypes, guiding architecture choices, and personally developing AI solutions — so 15-2051 (Data Scientists) is a credible runner-up.
The role is based in Fremont, CA, which falls within the San Francisco Bay Area CBSA (41940, San Jose-Sunnyvale-Santa Clara). The salary range is explicitly stated as applicable to the 'California, San Francisco Bay Area' geography.
The posting is hybrid ('On-site Flex' or 'Virtual Flex'), not fully remote — candidates are expected on-site at least 1–3 days per week.
The Required Qualifications section names no specific named technologies or tools — only broad capability areas (AI/ML, end-to-end solution development, technical leadership). AI/ML is captured as the one concrete hard-gate skill.
GenAI, MLOps, and computer vision appear only under Preferred Qualifications or as illustrative examples of focus areas ('e.g., ML, GenAI, vision, optimization, agents, automation') in the strategy narrative — not as hard gates.
An advanced degree (MS or PhD) is listed under Preferred Qualifications only, so the degree requirement is set to None.
No specific years-of-experience figure is stated at the role level or for any individual technology.
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