AI/ML Software Engineer (U.S. Citizen Only)
Job highlights
Identified by Google from the original job post
Qualifications
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
We’re looking for a passionate and innovative AI/ML Software Engineer who can lead the development of CubeNexus’s spatiotemporal analytics capabilities
Advanced proficiency in Python with experience in ML frameworks like TensorFlow, PyTorch, or Scikit-learn
Proficiency and prompting skills with multiple AI platforms including but not limited to ChatGPT, Gemini, Claude, and Perplexity
Experience in developing and deploying AI Agents using Llama, trained LLMs, and built ML models
Strong understanding of geospatial data structures (e.g., ECEF, MGRS, TULSA) and hierarchical models
Familiarity with distributed systems and working with APIs for real-time data ingestion and processing
Expertise in algorithm optimization for querying large datasets efficiently
Bachelor’s degree (or equivalent experience) in Computer Science, AI/ML, or related fields
Responsibilities
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
You will design, train, and deploy machine learning models that harness the unique strengths of our TULSA framework
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
Job description
About Us
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.
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.
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
• Advanced proficiency in Python with experience in ML frameworks like TensorFlow, PyTorch, or Scikit-learn
• Proficiency and prompting skills with multiple AI platforms including but not limited to ChatGPT, Gemini, Claude, and Perplexity.
• Experience in developing and deploying AI Agents using Llama, trained LLMs, and built ML models
• Strong understanding of geospatial data structures (e.g., ECEF, MGRS, TULSA) and hierarchical models.
• Familiarity with distributed systems and working with APIs for real-time data ingestion and processing.
• Expertise in algorithm optimization for querying large datasets efficiently.
• Bachelor’s degree (or equivalent experience) in Computer Science, AI/ML, or related fields.
Preferred Skills
• Experience with ElasticSearch, MongoDB, or other NoSQL databases.
• Knowledge of geospatial AI applications in industries like aviation, telecom, or energy.
• Understanding of signal processing or GNSS-based systems.
• Security and compliance knowledge for handling sensitive data (e.g., DoD standards).