Senior Machine Learning Engineer - Maps Data

ower 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.

Responsibilities

• As a Senior Machine Learning Engineer, you will be a technical leader responsible for the entire lifecycle of our data intelligence systems.

• ARCHITECT AND OWN PRODUCTION ML SYSTEMS: Lead the full lifecycle of ML solutions from research and prototyping through deployment, monitoring, and large-scale optimization.

• Ensure reliability, efficiency, and measurable impact of production ML systems.

• DRIVE DATA INTELLIGENCE WITH ADVANCED MODELS: Develop and fine tune sophisticated models, including LLMs/transformers and computer vision models, to extract insights, detect anomalies, and improve geospatial data quality.

• Design and operationalize generative AI driven multi-agent systems capable of reasoning, evaluating, and self-improving at scale.

• LEAD MULTI-FUNCTIONAL INNOVATION: Collaborate with data engineers, product managers, and operations teams to translate complex business needs into scalable technical solutions.

• Integrate ML systems seamlessly into the broader Maps ecosystem to enhance navigation, search, and place experiences.

• ELEVATE ENGINEERING PERFECTION: Champion standard processes in ML engineering and MLOps, including reproducibility, monitoring, and CI/CD for ML.

• Mentor and guide other engineers, fostering a culture of technical rigor, innovation, and continuous improvement.

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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