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Apps Applied Scientist
Apple
H1B ✓Hybridsenior levelPosted April 27, 2026
About the Role
The Applied Scientist will design and implement sophisticated machine learning and AI models to solve complex problems for creative applications. They will build end-to-end ML pipelines and collaborate with cross-functional teams to deploy intelligent solutions into production.
Requirements
Candidates must hold a PhD or MS in a quantitative field with several years of relevant experience in applied AI and statistical modeling. Proficiency in Python and experience with large-scale data systems and production-level AI deployment are required.
Full Job Description
We’re idealists. Inventors. Forever tinkering with products and processes, always on the lookout for better. Whether you work at our global offices, offsite, or even at home, a job at Apple will be demanding. But it also rewards forward-thinking, creative thinking and hard work. And none of us here would have it any other way. Does an exciting, dynamic, and fast-paced environment catch your attention? Do you like puzzles and determining solutions that are not obvious? Terrific! Consider joining our team! The Applications team is looking for an outstanding Applied Scientist who will strengthen our team’s capabilities in statistical modeling, machine learning, and foundational AI development. This role will drive innovation in building scalable ML and AI solutions that enhance our product intelligence, improve automation, and expand our AI-driven
capabilities across business domains.
The Applied Scientist will work on designing, developing, and implementing sophisticated machine learning and AI models to solve complex problems, particularly for creative applications like our image editing apps. The role involves building end-to- end ML pipelines, prototyping novel AI-powered features, developing AI tools, and collaborating closely with engineering, product, and marketing partners to bring intelligent solutions into production. The ideal candidate combines deep technical expertise in machine learning, statistical modeling, and AI framework development with strong problem-solving and interpersonal skills, ensuring effective collaboration and measurable impact in a fast-paced environment.
PhD in Computer Science, Statistics, Mathematics, or a related quantitative field with 3+ years of relevant experience; or MS with 5+ years of experience in applied AI, machine learning, or statistical modeling. 3+ years of programming proficiency with Python for data science and AI (e.g., Pandas, Scikit-learn, NumPy). 3+ years of hands-on experience applying statistical modeling and machine learning algorithms for supervised and unsupervised learning (classification, regression, clustering, etc.). 3+ years of experience working with large-scale data and distributed systems (e.g., Hadoop, Spark). Working familiarity with causal inference models and techniques. Hands-on experience deploying AI/ML models into a production environment. Experience with LLM fine-tuning, prompt engineering, or retrieval-augmented generation (RAG). Experience with rapid prototyping, reproduction, and validation of research ideas. Experience developing or contributing to AI frameworks, APIs, or internal tools used by other teams. Excellent presentation skills, distilling sophisticated analysis and concepts into concise business-focused takeaways.
We prefer a strong product sense and a passion for user experience. Strong product sense and a passion for user experience. Experience developing AI tools, frameworks, or APIs to support model deployment or LLM-based applications.
Description
The Applied Scientist will work on designing, developing, and implementing sophisticated machine learning and AI models to solve complex problems, particularly for creative applications like our image editing apps. The role involves building end-to- end ML pipelines, prototyping novel AI-powered features, developing AI tools, and collaborating closely with engineering, product, and marketing partners to bring intelligent solutions into production. The ideal candidate combines deep technical expertise in machine learning, statistical modeling, and AI framework development with strong problem-solving and interpersonal skills, ensuring effective collaboration and measurable impact in a fast-paced environment.
Minimum Qualifications
PhD in Computer Science, Statistics, Mathematics, or a related quantitative field with 3+ years of relevant experience; or MS with 5+ years of experience in applied AI, machine learning, or statistical modeling. 3+ years of programming proficiency with Python for data science and AI (e.g., Pandas, Scikit-learn, NumPy). 3+ years of hands-on experience applying statistical modeling and machine learning algorithms for supervised and unsupervised learning (classification, regression, clustering, etc.). 3+ years of experience working with large-scale data and distributed systems (e.g., Hadoop, Spark). Working familiarity with causal inference models and techniques. Hands-on experience deploying AI/ML models into a production environment. Experience with LLM fine-tuning, prompt engineering, or retrieval-augmented generation (RAG). Experience with rapid prototyping, reproduction, and validation of research ideas. Experience developing or contributing to AI frameworks, APIs, or internal tools used by other teams. Excellent presentation skills, distilling sophisticated analysis and concepts into concise business-focused takeaways.
Preferred Qualifications
We prefer a strong product sense and a passion for user experience. Strong product sense and a passion for user experience. Experience developing AI tools, frameworks, or APIs to support model deployment or LLM-based applications.