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Machine Learning Engineer, Sales Engineering

Apple - Austin Metro Area, United States of America

Posted Feb 18, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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Not verified last checked Jun 13, 2026
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401(k) match
Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.

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Weekend work
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Application

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About this role

Machine Learning Engineer, Sales Engineering Austin Metro Area, United States of America Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other's ideas stronger. Apple's Sales Engineering team is shaping the future of Channel Sales with innovative, high-impact applications. We're looking for a Machine Learning Engineer to help us design and build the next generation of intelligent systems that power Apple's global partner ecosystem. In this role, you'll develop and deploy machine learning solutions while leveraging generative AI and advanced ML capabilities to deliver scalable, production-ready systems that accelerate strategic, high-impact initiatives across Apple Channel Sales. If you're passionate about applying AI to solve complex business problems, experimenting with emerging GenAI technologies, and building products that make a real difference, join our collaborative team and help us move fast on game-changing ideas. Apple's Sales Engineering Rapid Application Development (RAD) team is looking for a Machine Learning Engineer to build intelligent, scalable solutions that power Apple's global Channel Sales. You'll leverage generative AI and advanced machine learning technologies to deliver high-performance, production-ready systems that drive measurable business impact. The ideal candidate blends deep ML expertise

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