Applied Scientist focused on causal inference, statistics, and machine learning to optimize marketing channels and product performance within Apple Services.
Responsibilities
Design, develop, and deploy causal inference and AI/ML solutions for marketing effectiveness
Define technical vision, strategy, and roadmap for AIML initiatives
Collaborate with cross-functional partners to deliver customer and business value
Requirements
Master’s degree in Statistics, Economics, Mathematics, Machine Learning, Computer Science, Engineering, or a related technical field
Nice to have: PhD in related field
Nice to have: Hands‑on experience leveraging Generative AI to improve productivity and generate new insights
Senior Machine Learning Research Engineer within the Siri team focusing on efficient machine learning for dialog systems and foundation models, including NLU and speech integration.
Responsibilities
Tackle core problems in efficient machine learning for effective dialog systems and foundation models
Work on natural language understanding and multi-turn context tracking
Integrate speech, text, and other modalities
Build technology centered around users and their needs
An SRE on Apple Data Platform operates and supports a massive multi-cloud platform for internal data and AI products, focusing on infrastructure, automation, and ML/AI platform services reliability.
Responsibilities
Running incident response
Providing hands-on support to internal teams
Partnering with developers to make cutting-edge services like Spark, Flink, Airflow, Ray, Notebooks and LLM-based agent platforms reliable at scale
Building deep reliability roadmaps
Automating manual operations through scripting or tooling
The role will be embedded within a core business area (growth, product, AI and automation, or strategic partnerships) to own the analytical function end-to-end.
Locations (4)
New York, New York, United States
Palo Alto, California, United States
Chicago, Illinois, United States
Toronto, Ontario, Canada
Responsibilities
Define the right problems and understand what business question an analysis is answering
Define metrics, build reports, run analyses, design experiments, and surface data insights
Bring recommendations to counterparts in product, growth, finance or operations
The Data Scientist will be embedded within a core business area (growth marketing, product delevop, AI and automation, or strategic partnerships) owning the analytical function end-to-end.
Locations (4)
New York City, New York, United States
Palo Alto, California, United States
Chicago, Illinois, United States
Toronto, Ontario, Canada
Responsibilities
Define the right problems and understand what business question it's answering
Define metrics, build reports, run analyses, design experiments
Surface data insights that move team's key metrics
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