Data Scientist - Health AIML at Apple

Cupertino, California, United States -

Full Time

Start Date

Immediate

Expiry Date

27 Aug, 26

Salary

0.0

Posted On

29 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Statistical Data Analysis, A/B Testing, SQL, Spark, Python, R, Scala, Large Language Models, Prompt Engineering, Fine-tuning, Synthetic Data Generation, Model Optimization, Data Querying, Cross-functional Collaboration

Industry

Computers and Electronics Manufacturing

Description

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 We are looking for a highly technical and experienced data scientist who can work embedded with engineering to help design, execute, and analyze manual and LLM based evaluations of health AI models and agentic experiences. MINIMUM QUALIFICATIONS 5+ years of experience in data science, machine learning, and analytics, including statistical data analysis and A/B testing. Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data. Strong programming skills, including data-querying skills (SQL and/or Spark, etc.) and experience with a scripting language for data processing and development (e.g., Python, R, or Scala). Excellent collaboration skills to achieve impactful results by working effectively with diverse cross-functional teams, including PMs, engineers, data scientists, and others. B.S. in Machine Learning, Computer Science, Statistics, Operations Research or other quantitative fields. PREFERRED QUALIFICATIONS Applicants have a good understanding of large language model (LLMs), including their architecture, training methods, prompt engineering and fine-tuning for specific tasks. Hands-on experience in applying LLMs to solve technical problems, such as data analysis, data automation, synthetic data generation, with proven ability to optimize model performance for accuracy and efficiency. Ph.D. in machine learning, computer science, statistics, operations research or other quantitative fields. 10+ years of relevant work experience.

Responsibilities

Design, execute, and analyze manual and LLM-based evaluations for health AI models and agentic experiences. Work embedded with engineering teams to solve real-world health domain problems and optimize model performance.