Senior Staff Machine Learning Engineer

Overview

Own the AI platform and tooling roadmap for Memory Solutions, streamline developer onboarding, and partner across IT, Security and Legal to turn responsible AI guardrails into business impact.

What you'll do

• Shape the AI platform and tooling roadmap for Memory Solutions, aligned with business priorities.
• Coordinate access to approved AI tools, infrastructure and services.
• Partner with IT, security and legal to establish practical, risk-based AI governance.
• Define standards for responsible AI use, data protection and solution integration.
• Leverage existing enterprise capabilities before introducing custom platforms.
• Align vendors and internal stakeholders on capabilities, licensing and cost efficiency.
• Equip community builders with reusable components, templates and technical guidance.
• Enable experimentation through clear guardrails and streamlined onboarding.
• Coordinate technical readiness and security review before production handover.
• Track platform adoption, access reliability, cost efficiency and governance effectiveness.

What you'll need

• Bachelor's or Master's degree in Computer Science, Information Technology, AI, Engineering, or a related field.
• 7 years of relevant work experience in enterprise technology, solution architecture, or AI/ML, including at least 2 years leading LLM, Generative AI, RAG, or enterprise AI platform initiatives.
• Strong understanding of enterprise AI architectures, foundation models and integration patterns, with experience assessing and reusing existing capabilities before introducing custom platforms.
• Hands-on experience integrating AI solutions with enterprise systems, APIs and data sources, including identity and access management and appropriate data protection controls.
• Experience establishing practical, risk-based AI governance and responsible AI standards in partnership with IT, security and legal teams.
• Experience in software engineering and AI application delivery, including CI/CD, deployment practices, technical readiness assessments and production handover to accountable engineering and operations teams.
• Good understanding of enterprise cloud infrastructure and AI services, with the ability to assess vendor capabilities, licensing, access reliability and cost efficiency.
• Experience shaping platform and tooling roadmaps and enabling community builders through reusable components, templates, technical guidance and streamlined onboarding.
• Highly motivated, structured and methodical, with a high degree of self-initiative and an analytical approach to tracking platform adoption and governance effectiveness.
• Team player with strong communication and cross-cultural collaboration skills, able to align stakeholders and work with the fellow co-lead as an enabler rather than the default implementation or operations owner.

Nice to have

• Preferred domain knowledge: Semiconductor engineering, enterprise IT, and secure technology enablement across engineering and business functions.