What are the responsibilities and job description for the AI/ML Software Engineer (U.S. Citizen Only) position at CubeNexus Inc?
About Us
Due to the nature of our work, including potential collaborations with defense and government projects, applicants must be U.S. Citizens. This requirement ensures compliance with federal regulations and eligibility to work on sensitive projects involving national security. Proof of U.S. citizenship will be required during the hiring process.
CubeNexus is revolutionizing data structuring by building the foundation of the true spatial web. By leveraging our proprietary CubeNexus TULSA (Time United Location System Address) framework, we are integrating spatiotemporal data into a unified system with unparalleled precision. This is an opportunity to join a pioneering team redefining how data is stored, queried, and analyzed—starting with applications in aviation, oil and gas, and telecom, with the potential to expand into classified DoD projects in the near future.
As an AI / ML Software Engineer, you will play a pivotal role in designing the AI-driven functionality that underpins CubeNexus . This is your chance to influence the future of geospatial intelligence and create a scalable platform with the potential to transform industries worldwide.
Your Role
We’re looking for a passionate and innovative AI / ML Software Engineer who can lead the development of CubeNexus’s spatiotemporal analytics capabilities. You will design, train, and deploy machine learning models that harness the unique strengths of our TULSA framework.
Key Responsibilities
- AI Agent Development : Build and optimize CubeNexus AI agents and embedded AI applications to process and analyze spatiotemporal data at scale.
- Full-Stack Engineering : Back-end, front-end, and infrastructure architecting and build out of the CubeNexus platform
- Algorithm Design : Develop novel machine learning algorithms for recursive, hierarchical spatiotemporal data analysis and prediction.
- Data Pipeline Integration : Design and implement data pipelines to process real-time and static data sources, ensuring compatibility with CubeNexus TULSA grains.
- Model Optimization : Train and optimize ML models for efficiency in querying and interacting with the CubeNexus platform.
- Cross-Industry Application : Collaborate with domain experts to adapt AI capabilities for aviation, oil and gas, and telecom industries.
- Future DoD Expansion : Ensure AI systems are modular and secure, enabling future integration into classified military applications.
What You Bring
Required Skills
Preferred Skills
