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Apple Senior Machine Learning Engineer - Semantics Apple Ads United States, Texas, Austin 265034802
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The role requires experience in development, fine-tuning, evaluation, and application of large language models (LLMs) to solve complex natural language processing tasks. The ideal candidate will have working experience in machine learning, data engineering, and prompt design to build scalable, intelligent systems that can understand, generate, and reason with human language. Experience in areas such as predictive modeling (classification and regression), optimization, industrial engineering, demand forecasting, and time-series forecasting is a plus. Deep understanding and ability to compare predictive models, evaluate their strengths and weaknesses in a particular context, and interpret and explain model results to a broad group of technical and non-technical stakeholders are also a plus. Driven candidates will work across use cases such as summarization, classification, knowledge extraction, and prediction, often partnering with product, and engineering, bring LLM-powered solutions into production.
- Bachelor's or equivalent experience in computer science, mathematics, or another quantitative field
- Command over Python and common and common ML/NLP libraries as well as SQL
- Comfort with cloud technologies such as AWS and Snowflake.
- Experience with Big Data tools such as Hadoop, Spark and PySpark.
- Experience in applying NLP/LLM to real-world problems plus experience in quantitative analysis including regression, classification, linear optimization, supply chain analytics, and time-series analyses.
- Ability to communicate the results of analyses in a clear and effective manner with product and leadership teams to influence the overall strategy of the product.
- Ability to partner with engineering, meet the data needs of the business, find creative analytical solutions, and develop initial prototypes to address business problems.
- Experience with end-to-end implementation of a model prototype specifically training, processing, feature engineering, evaluating model outputs, and putting models into production.
- Masters' degree, Ph.D. or equivalent experience in a quantitative field.
- Experience in the digital advertising industry or a related field and/or experience with demand forecasting
- Willingness to learn, both technically and in the domain of the data.
- Familiarity with packages like numpy, pandas, scikit-learn, and prophet
- Familiarity with job orchestration frameworks like git, Airflow, CI/CD, Kubernetes, Docker, Jenkins.
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