Senior Machine Learning Engineer

Join a passionate, dynamic team responsible for creating experiences that enable users to get help with-and discover all the things they love about-their Apple products. In this role, you will have the opportunity to join a team building applications, frameworks, and system-level experiences for hundreds of millions of users across the Apple ecosystem. The Instructional Products team is looking for a Senior Machine Learning Engineer to join a team building both internal and customer-facing features, applications, and tools. In this role, you'll be at the forefront of shaping personalized help and discovery experiences powered by state-of-the-art machine learning, generative AI, and agentic systems and modeling.

Description

As a Senior Machine Learning Engineer, you will guide the end-to-end delivery of multiple ML and generative AI initiatives. Your work will span defining technical strategy, shaping data pipelines, building and deploying models, and iterating post-launch. You will partner closely with product, design, engineering, and content teams to create features that are contextually aware and deeply aligned with Apple's user experience principles. You'll contribute to the development of LLM-powered systems, including prompt engineering, fine-tuning on domain-specific data, and Retrieval-Augmented Generation (RAG) architectures. Experience with agent-based systems-such as multi-step reasoning, tool use, and task planning-is highly valued. Your success in this role will depend on a strong understanding of how users interact with Apple's products, and on your ability to translate ML innovations into intuitive, intelligent experiences that scale.

• At least 3 years of professional software or ML experience delivering customer-facing features.
• Deep knowledge of modern ML concepts and techniques and hands-on expertise with at least one major framework (PyTorch, TensorFlow, or JAX).
• Demonstrated expertise in training and debugging machine learning systems, including data processing, model evaluation, and systematic error analysis.
• Strong software engineering skills in Python.
• Experience shipping models to productions, including model compression, quantization, and real-time inference.
• Excellent written and verbal communication; able to explain complex ML concepts to colleagues who do not have an ML background.

• MS/PhD in Machine Learning or equivalent industry experience.
• Experience in designing or deploying agent-based systems for reasoning, task decomposition, or tool orchestration.
• Passion for crafting intuitive user experiences and a track record of turning data insights into product features.
• Comfortable thriving in a fast-moving environment with shifting priorities and multiple concurrent projects.