
Senior Machine Learning Engineer
3 days ago
Description
As a Machine Learning Engineer on the Maps Data Engineering team, you'll design and deploy advanced models that fuse satellite imagery, aerial photos, behavioral signals, rich map metadata, and hundreds of internal data sources to power next-generation user experiences. You'll also pioneer the development of generative AI–driven multi-agent systems capable of dynamic reasoning, evaluation, and self-improvement—scaling the accuracy, precision, and quality of map data that millions of users rely on every day.
This role offers the opportunity to solve some of the most complex real-world challenges at the intersection of geospatial intelligence, computer vision, large language models, and generative AI.
At Apple, we create products that enrich people's lives; and we believe even the smallest moments, like arriving confidently at the right destination, are part of that promise. As a member of the Maps Data Engineering team, you'll help transform intricate geospatial systems into seamless, intuitive experiences; turning advanced technology into everyday magic for hundreds of millions of users worldwide.
Minimum Qualifications
5+ years of experience in machine learning engineering or applied data science, with a consistent record of delivering production-grade ML systems.
8+ years of software product engineering experience.
Strong background in machine learning, computer vision, NLP, or generative AI, with hands-on expertise applying these techniques to large-scale data.
Deep familiarity with LLMs, transformers, and the HuggingFace ecosystem; ability to fine-tune, optimize, and deploy models in production.
Proven grounding in statistical modeling, design, and predictive analytics to drive decisions.
Expert-level proficiency in Python and command of data science libraries (e.g., NumPy, Pandas, Polars, Scikit-learn) and ML frameworks (PyTorch, TensorFlow).
Proficiency in data visualization for analysis, model diagnostics, and communicating sophisticated findings (e.g., Matplotlib, Seaborn, Plotly).
Excellent communication, leadership, and mentoring skills, with the ability to guide junior engineers and collaborate effectively across diverse teams.
Preferred Qualifications
A track record of publications in credible machine learning conferences (e.g., NeurIPS, ICML, ACL) or relevant journals
Contributions to publicly available models or a strong performance record on Kaggle or other machine learning competitions.
Past experience working directly with geospatial data, mapping technologies, or location-based services.
A strong conceptual understanding of distributed data and compute systems, event streaming platforms (e.g., Kafka), and modern data storage formats.
Advanced degree (MS/PhD or equivalent experience) in Computer Science, Machine Learning, AI, or related field or equivalent practical experience.
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