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Apple Machine Learning Engineer Maps United States, California, Cupertino 339477769
Today
As a Machine Learning Engineer on the Arrival Experience team, you’ll design and deploy models that blend satellite and aerial imagery, behavioral signals, and map metadata to deliver precise, intuitive destination guidance. You’ll also develop generative AI-based multi-agent systems that can dynamically reason, evaluate, and improve guidance quality at scale.
- Build and deploy ML models that integrate imagery, spatial context, and user behavior to enhance arrival accuracy- Design and implement generative AI-based multi-agent systems that evaluate and improve arrival experiences- Evaluate models using both automated metrics and real-world feedback, continuously iterating for quality- Stay informed on advances in computer vision, generative AI, and applied machine learning to explore new approaches and keep the system adaptive and future-ready
- MS or PhD in Computer Science, Machine Learning, or a related field.
- 2+ years of hands-on experience in machine learning, particularly in computer vision or multimodal model development
- Experience building and deploying transformer-based architectures, including Vision Transformers (ViT), or multimodal vision-language models such as CLIP
- Familiarity with multi-agent system design and orchestration frameworks, including the use of Model Context Protocol (MCP), A2A (agent-to-agent) communication systems, or LangGraph for generative agent workflows
- Proficiency in Python with deep expertise in PyTorch for model development and deployment
- Experience working with large-scale datasets and building scalable training or inference pipelines
- A self-starter with a go-getter attitude, able to work around data limitations or organizational constraints and continue making progress
- Excellent problem-solving skills with the ability to approach ambiguous problems creatively
- Strong collaboration and communication skills with a track record of working effectively across teams
- Commitment to fostering an open, inclusive, and team-oriented work environment
- Demonstrated success applying generative AI to production systems beyond prompt engineering
- Familiarity with extracting and refining polygonal features from imagery, including post-processing techniques such as the Marching Squares algorithm or similar contour extraction methods
- Experience working with geospatial data formats such as GeoTIFF, raster maps, shapefiles, or GeoJSON
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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