Sr. Data Visualization Engineer

Help the experimentation platform team in Apple Services Engineering implement intuitive dashboards that make complex evaluation flows and metrics easily consumable by ML Engineers, Product, and Leadership. This is a great opportunity for someone passionate about adding value to large data sets and empowering stakeholders to make decisions. This role will focus on the software engineering aspects, such as building robust, scalable data visualization applications, custom tools, and platforms, and integrating them with existing data pipelines and cloud platforms. The tools you build will be in the daily workflow of our engineers and data scientists who are improving features and experiences for Apple customers. You will be on the team responsible for building tools that coordinate hill climbing on ML models and features and creating intuitive interfaces that display metrics and analysis of how those models and features perform as well as highlight key ways those features can improve.

This role focuses specifically on designing and developing the visual representations of data, such as interactive dashboards, charts, graphs, and infographics. They bridge the gap between raw data and informed decision-making, using both design principles and technical skills (e.g., JavaScript charting libraries, D3.js).

A proven track record of communicating effectively via compelling visuals that create a clear narrative for the intended audience and ensure user friendly interfaces. Proficiency in designing and developing visual representations of key metrics that may require charts, graphs, and interactive dashboards. Ability to collaborate closely with research scientists and data science teams to translate complex analytical findings into clear, actionable visualizations that drive decision-making. At least 5 years of experience developing intuitive data visualizations. Bachelors in relevant field or equivalent experience.

The ability to work closely with ML Engineers building both features and evaluation services. Foundational knowledge in statistics and uncertainty quantification to accurately represent data variability, confidence intervals, and probabilistic outcomes in visual formats. Proven ability to write readable and maintainable code. Excellent debugging, analytical, problem solving, and interpersonal skills. Proficiency with languages such as Python, R, Ruby, and SQL to query data sets. ML Engineering exposure is a plus.