Cartesian is looking to solve the problem of in-store inventory visibility in the $35T global retail industry by building spatial intelligence for indoor environments to drive operational efficiency.
Requirements
- Proficiency in writing high-quality, maintainable production code, with strong software engineering fundamentals) testing, version control, CI/CD, performance optimization)
- Experience working with PyTorch, Ray
- Experience with cloud-based model training and inference
- Experience in optimizing and deploying ML models in mobile or edge devices
- Familiarity with FastAPI, Python
- Experience with Postgres, Blob Storage, Parquet
- Experience with Azure, Kubernetes, Helm
Responsibilities
- Design, develop, and deploy ML models for indoor positioning and perception.
- Optimize model architectures for performance and efficiency.
- Develop tools and datasets to benchmark performance in the real world and at scale.
- Translate research into production pipelines.
- Collaborate with engineering and product to ship features to enterprise customers.
Other
- BS/MS in computer science, electrical engineering, or related technical field
- 3+ years of practical industry experience building end-to-end deep learning systems
- Strong communication skills and proven ability to collaborate effectively with cross-functional teams
- Ability to work in fast-paced, dynamic environments and take pride in producing high-quality work
- Travel requirements not specified
