Apple is looking to solve the problem of providing precise and intuitive destination guidance to hundreds of millions of Apple Maps users, by making navigation more intelligent and context-aware.
Requirements
- 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
- 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
Responsibilities
- 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
- Work closely with product and engineering teams to bring model intelligence into user-facing features
- 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
Other
- 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
- 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
