Software Development Engineer

Apple•Sunnyvale, CA

About The Position

This role is an opportunity to join an exciting engineering team responsible for building next-generation health sensors and features. The engineer will be responsible for building new web-based monitoring and visualization platforms, extracting insights from sophisticated data sets, and developing intelligent automation to support multiple user studies per year. These studies range from focused studies with tens of participants to large-scale studies with thousands of participants. The work will directly impact the development of health-related features in Apple products. Data Integrity means ensuring the collection of high-quality data from health user studies through robust data analysis pipelines and operator-facing tools and dashboards. The engineer will work closely with cross-functional teams to identify user study problems and advise decision-making through data analysis. This role focuses on building new data and platform solutions to improve the usability of our systems for large-scale user studies that gather critical data to design and qualify Apple's health software products. The engineer will design and build new web-based monitoring and visualization tools that give study teams real-time insight into study health and data quality, serving multiple concurrent studies that range in scale from tens to thousands of participants. The role involves leveraging LLM-based agentic workflows not only within the product itself by integrating OpenAI/Anthropic APIs to create richer, smoother user experiences in study tools, but also within the development lifecycle, using LLMs in a closed-loop workflow spanning planning, architecture, design review, implementation, PR generation, and deployment. A key part of this role is partnering directly with the researchers, engineers, and study operations teams who use the tools daily. The engineer will deeply engage with stakeholders to understand their specific needs, gather feature requests, and prioritize improvements via established planning processes all while upholding Apple's privacy-first policies when handling sensitive health data. The engineer will own the relationship between the platform and the people who depend on it.

Requirements

Bachelor’s degree in Computer Science, Engineering, Informatics, or equivalent with relevant proven experience with biomedical, health, or sensitive data.
3+ years of software engineering experience.
Strong software development skills, with proficiency in Python.
Experience integrating LLM-based functionality (e.g., OpenAI, Anthropic APIs) into production web tools to create richer, smoother user experiences.
Experience leveraging LLMs in a closed-loop development workflow — from planning and architecture, to design review, to implementation, to generating pull requests, to deployment.

Nice To Haves

7+ years of software engineering experience.
3+ years in backend web service development.
Experience building web application backends for data monitoring and visualization (e.g., Flask, FastAPI, or similar frameworks; REST APIs; serving data to frontend dashboards).
Demonstrated skill and experience with distributed data processing systems such as PySpark and SparkSQL.
Demonstrated experience leading design reviews, mentoring engineers, and influencing technical/product roadmaps.
Familiarity working with systems such as blob storage, elastic compute, and virtual instances.
Experience with technologies such as Delta Lake, AWS; container orchestration (Kubernetes or similar); workflow orchestration (Apache Airflow or similar) are all a benefit.
Experience with tools such as Git, Docker, Jupyter notebooks, Linux command line.
Experience with basic time series data analysis such as trend detection, anomaly identification, signal processing fundamentals.
Demonstrated ability to engage directly with tool users and stakeholders to gather requirements, understand workflows, and translate needs into platform features and improvements.
Experience working with sensitive or regulated data under strict privacy requirements.

Responsibilities

Building new web-based monitoring and visualization platforms.
Extracting insights from sophisticated data sets.
Developing intelligent automation to support multiple user studies.
Building backend systems.
Developing visualization tools.
Improving platforms used for research and development.
Ensuring the collection of high-quality data from health user studies through robust data analysis pipelines and operator-facing tools and dashboards.
Working closely with cross-functional teams to identify user study problems and advise decision-making through data analysis.
Building new data and platform solutions to improve the usability of systems for large-scale user studies.
Designing and building new web-based monitoring and visualization tools that give study teams real-time insight into study health and data quality.
Leveraging LLM-based agentic workflows within the product and development lifecycle.
Partnering directly with researchers, engineers, and study operations teams.
Engaging with stakeholders to understand specific needs, gather feature requests, and prioritize improvements.
Upholding Apple's privacy-first policies when handling sensitive health data.