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GenAI Research Engineer
Apple
- Location
- Onsite (Cupertino, California · Seattle, Washington)
- Employment
- Full-time
- Level
- Senior Level
Posted 2 weeks ago
About the Role
The Health Personalization team at Apple is developing AI-driven health experiences that provide users with actionable insights and support their wellness goals. This role involves developing and improving Generative AI systems for real-world health applications, collaborating with scientists and engineers to build high-quality, scalable systems aligned with human intent.
Skills
Python
Generative AI
Machine Learning
Large Language Models
Supervised Fine-Tuning
Reinforcement Learning from Human Feedback
Natural Language Understanding
Health Informatics
A/B Testing
Data Generation
Knowledge Retrieval
Full-stack Deployment
Model Evaluation
Scientific Experimentation
Memory Representation
Planning
Full job details
The Health Personalization team builds outstanding technologies to support AI-driven health experiences that provide our users with understandable, actionable information about their health and wellbeing, and support them to achieve their health and wellness goals. As part of the larger Sensor Software & Prototyping team, we take a multimodal approach using a variety of sensors and user data signals across hardware platforms, such as camera, wearables, and natural language user input. We are committed to building deeply personal features that understand, anticipate, and adapt to users’ behaviors and uphold Apple’s deep commitment to privacy as a fundamental human right. Our team values expertise, innovation, and inclusivity. Come join us!
In this role, you will develop, evaluate, and continuously improve Generative AI systems for real-world health and wellbeing applications. You’ll apply deep expertise in health-focused machine learning alongside rigorous evaluation methodology. Your work will directly shape customer-facing health products by turning evaluation results into scalable pipelines that drive data-informed model improvements across the full ML lifecycle. You’ll collaborate with a fast-growing team of top scientists and engineers to build generative systems that meet the highest standards of quality, reliability, and alignment with human intent.
BS and a minimum of 10 years relevant industry experience Proficiency in Python and ability to write clean, performant code and collaborate using standard software development practices. Technical expertise and hands-on experience crafting and evaluating machine learning solutions for user-facing applications. Experience applying a scientific approach to drive machine learning innovation: developing hypotheses, designing experimentation strategies, and guiding data generation / collection / evaluation (e.g. user studies, annotation workflows, A/B tests).
MS or PhD in a detailed quantitative field such as computer science, mathematics, statistics, economics, health informatics, or similar and 5 years relevant industry experience Strong communication skills, comfort working with multiple engineering teams on complex projects, and experience contributing to an inclusive team culture. Technical expertise in generative AI domains, such as large language model architectures, memory representation, planning, knowledge retrieval, natural language understanding. Hands-on experience developing complex generative AI systems in an applied setting, e.g. experience with post-training techniques like supervised fine-tuning, adapter training, and reinforcement learning from human feedback. Experience with LLM-based evaluation systems and rigorous, evidence-based approaches to test development, e.g. quantitative and qualitative test design, reliability and validity analysis. Customer-focused mindset with experience or strong interest in building consumer digital health and wellness products. Knowledge of health informatics or experience with complex health data sources (e.g. EHRs, medical ontologies, wearables) Experience with building and deploying performant and scalable systems (full-stack)
Description
In this role, you will develop, evaluate, and continuously improve Generative AI systems for real-world health and wellbeing applications. You’ll apply deep expertise in health-focused machine learning alongside rigorous evaluation methodology. Your work will directly shape customer-facing health products by turning evaluation results into scalable pipelines that drive data-informed model improvements across the full ML lifecycle. You’ll collaborate with a fast-growing team of top scientists and engineers to build generative systems that meet the highest standards of quality, reliability, and alignment with human intent.
Minimum Qualifications
BS and a minimum of 10 years relevant industry experience Proficiency in Python and ability to write clean, performant code and collaborate using standard software development practices. Technical expertise and hands-on experience crafting and evaluating machine learning solutions for user-facing applications. Experience applying a scientific approach to drive machine learning innovation: developing hypotheses, designing experimentation strategies, and guiding data generation / collection / evaluation (e.g. user studies, annotation workflows, A/B tests).
Preferred Qualifications
MS or PhD in a detailed quantitative field such as computer science, mathematics, statistics, economics, health informatics, or similar and 5 years relevant industry experience Strong communication skills, comfort working with multiple engineering teams on complex projects, and experience contributing to an inclusive team culture. Technical expertise in generative AI domains, such as large language model architectures, memory representation, planning, knowledge retrieval, natural language understanding. Hands-on experience developing complex generative AI systems in an applied setting, e.g. experience with post-training techniques like supervised fine-tuning, adapter training, and reinforcement learning from human feedback. Experience with LLM-based evaluation systems and rigorous, evidence-based approaches to test development, e.g. quantitative and qualitative test design, reliability and validity analysis. Customer-focused mindset with experience or strong interest in building consumer digital health and wellness products. Knowledge of health informatics or experience with complex health data sources (e.g. EHRs, medical ontologies, wearables) Experience with building and deploying performant and scalable systems (full-stack)
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