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Apple AIML - Senior Machine Learning Engineer Siri Information Intelligence United States, California, Cupertino 5437384
07.04.2025
As a Machine Learning Engineer within the Siri team, you will define new approaches for evaluating state-of-the-art ML based systems, conversational AI, and model interpretability. You will collaborate with different modeling teams, and product managers to conduct thorough evaluation and analysis of Apple Intelligence products and models, identifying areas for improvement and optimization. You will work with large amounts of real-world data to analyze and propose changes to the Siri user experience. You will ensure data quality throughout all stages of acquisition and processing, data wrangling, etc. Your expertise in defining and measuring the online and offline end-to-end metrics will help communicate, evaluate, and iterate on state-of-the-art deployed models and predictors
The team is searching for talented ML Engineers to work with a passionate, product-focused team to define new approaches for evaluating ML based systems, conversational AI, and model interpretability You will run experiments, statistically interpret data with a mind on causation, data visualization, plus designing, building, and evaluating models. You will work with large amounts of real-world data to analyze and propose changes to Siri user experience. You will ensure data quality throughout all stages of acquisition and processing, data wrangling, etc. Your expertise in defining and measuring the online and offline end-to-end metrics will help communicate, evaluate, and iterate on state-of-the-art deployed models and predictors.
- 7+ years of professional work experience applying machine learning to real-world problems, and crafting scalable and effective data solutions.
- Strong domain knowledge in at least one of the following: NLP, conversational AI, speech recognition
- Excellent programming skills in Python and data analytical skills.
- Excellent problem solving, critical thinking, and communication skills.
- Strong attention to detail. Proven ability to dive into data to discover hidden patterns and conduct error/deviation analysis
- Good experience with applying Big Data tools (MapReduce, Hadoop, Hive and/or Pig, Spark) to large quantities of textual data
- Domain knowledge in applied statistics and experimental design is big plus!
- Enthusiasm for continuing to learn state-of-the-art techniques in machine learning/data science
- Strong background in A/B testing procedure, causal analysis, and cohort analysis.
- Exposure to model interpretability techniques and their real-world advantages/drawbacks
- Good Conversational AI domain knowledge
- Experience working with end-to-end pipelines and/or crowd-sourced data labeling
- B.S., M.S. or Ph.D. in Computer Science, Electrical Engineering, Statistics, Applied Math, Physics or related fields is preferred
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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