Staff Machine Learning Engineer - Tools & Frameworks AI

Our team designs and builds ML solutions to transform how Apple and developers in the ecosystem approach developing quality software at scale. We are a team of applied scientists, infrastructure engineers, and machine learning engineers who work with NLP, computer vision, and multimodal domains to create AI-powered testing solutions. In this role, you will be responsible for developing novel ML approaches to challenging quality problems at scale. You'll work hands-on with a diverse set of ML techniques to find what actually works in production. You'll guide technical direction for the team, mentoring junior engineers while maintaining deep involvement in the code and experimentation yourself. Your technical judgment and understanding of both generative models and traditional ML methods will directly shape our product direction. You will be successful and feel fulfilled in our team if you enjoy tackling challenging problems with creative solutions, have strong intuition for what will and won't work in practice, and thrive in a collaborative team setting where you can both learn and teach. Design and implement novel ML solutions for testing and automation problems Provide technical leadership and mentorship on research directions Apply a broad range of ML techniques (LLMs, classical ML, computer vision, reinforcement learning) to identify the best approach for each problem Work cross-functionally with product teams, integration engineers, and other ML practitioners across Apple 5+ years of hands-on experience developing machine learning systems in production environments Strong programming skills with demonstrated ability to write production-quality ML code Proven track record working with multiple ML paradigms including modern and traditional methods MS or PhD in Computer Science, Machine Learning, or equivalent professional experience Experience with classical ML techniques, reinforcement learning, or probabilistic modeling in addition to deep learning Experience in NLP, computer vision, or multimodal ML applications Track record of technical mentorship or leading complex ML projects Familiarity with Apple development ecosystem and frameworks Experience with testing, software quality, or developer tools

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