Machine Learning Engineer - Health AIML

Apple·Seattle, Washington, United States·posted 4d ago · last seen 43m ago

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About interviewing at Apple

One of tech's least standardized loops: you interview for a specific team, and every stage belongs to it. Recruiter/hiring-manager screen, one to three 45–60 minute Coderpad coding screens, a system design round shaped by Apple's reliability and privacy constraints, and a behavioral round — then a panel debrief. There is no central question bank; questions map to the team's real stack.

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Description

Summary

The Health AI team is at the forefront of machine learning and health science at Apple. We are a close-knit team of highly accomplished, deeply technical research scientists, software engineers, and machine learning engineers passionate about delivering innovative technologies that impact millions of users. We are looking for a senior engineer excited about solving real-world problems in the health domain that make a difference in our customers' lives.

Description

In this role, you will use your skills and experience in software engineering, machine learning, deep learning, and generative AI to design, implement, tune, and evaluate machine learning models and systems. You will solve ambitious problems involving unique data and high-impact products, including state-of-the-art generative AI technologies. The successful candidate should possess excellent interpersonal skills and the ability to work cross-functionally to rapidly apply engineering best practices and novel research techniques at the intersection of Health, ML, and consumer products.

Minimum Qualifications

10+ years of overall software development experience. Experience leading a team and/or a proven track record of cross-functional collaboration to deliver customer-facing features with machine learning capabilities in production. BS/MS/Ph.D. in Computer Science, Computer Engineering, Machine Learning, or related fields (or equivalent qualification).

Preferred Qualifications

Ph.D. in Computer Science, Machine Learning, or a related field. Strong background in generative models, natural language processing (NLP), and large language models (LLMs). 5+ years of hands-on experience in state-of-the-art machine learning and deep learning applied to large-scale datasets and/or production applications. Proficiency developing and working with large-scale models using modern machine learning packages (e.g., TensorFlow, PyTorch, Jax, Huggingface). Proficiency in building and troubleshooting modern agentic systems (prompt tuning, routing, planning, multi-agent, RAG, tool use, memory management, etc.). Experience with healthcare data, products, and workflows. Ability to thrive in a fast-paced environment, deal with uncertainty, and adapt to new and changing requirements. Proven track record of contributing to diverse teams in a collaborative environment. A passion for building outstanding and innovative products. This position involves a wide variety of interdisciplinary skills

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