Staff Specialist Machine Learning Engineer

Overview

Drive grassroots AI innovation across Memory Solutions by building and validating timeboxed experiments, and scaling proven workflows into funded production solutions backed by clear ROI, data readiness, and cross-functional governance.

What you'll do

• Build and prioritize an AI use-case portfolio for Memory Solutions aligned with engineering and business needs.
• Partner with domain leaders to identify high-value workflow improvement opportunities against value, feasibility, data readiness, and risk.
• Mobilize a voluntary network of AI champions, builders, and domain experts.
• Coach contributors through focused, timeboxed experiments using approved tools.
• Connect domain expertise, relevant data, and technical capabilities to accelerate solutions.
• Establish success criteria and validate results with accountable domain owners.
• Drive adoption through demonstrations, knowledge sharing, and reusable solutions.
• Secure funded ownership, engineering capacity, and support before production adoption.
• Report realized impact and recommend which initiatives to scale, refine, or stop.

What you'll need

• Bachelor's or Master's degree in Computer Science, Data Science, AI, Engineering, Business Informatics, or a related field.
• 5 years of relevant work experience in AI/ML, digital transformation, or technology-driven process improvement, including at least 2 years leading LLM, Generative AI, RAG, or AI application initiatives.
• Strong understanding of Generative AI capabilities, limitations, and application patterns, with experience translating domain needs into a prioritized AI use-case portfolio.
• Experience assessing use cases against business value, technical feasibility, data readiness, and risk, in close partnership with domain leaders and technical experts.
• Hands-on experience with AI prototyping, prompt engineering, and solution evaluation using approved enterprise tools.
• Experience guiding contributors through focused, timeboxed experiments and connecting domain expertise, relevant data, and technical capabilities without becoming the default implementer.
• Experience defining baselines and success criteria, validating measurable outcomes with accountable domain owners, and recommending which initiatives to scale, refine, or stop.
• Experience in project and change management, including securing funded ownership, engineering capacity, and support arrangements before production adoption.
• Highly motivated, structured, and entrepreneurial, with the ability to mobilize a voluntary network of AI champions and accelerate adoption through demonstrations, knowledge sharing, and reusable solutions.
• Team player with strong communication and cross-cultural collaboration skills, able to report realized impact, influence stakeholders without direct authority, and work with the fellow co-lead as an enabler and multiplier.

Nice to have

• Semiconductor engineering workflows and business processes domain knowledge, including opportunities to improve productivity, quality, and innovation through AI.
• Proficiency in Python and familiarity with GenAI frameworks.