Software Engineer - AI Platforms & Edge Computing

At MatrixSpace, we are building technology that bridges the physical and digital worlds — combining embedded systems, radar sensing, cloud computing, and AI to unlock powerful real-world intelligence.

We’re looking for a software engineer to help build and scale our edge and cloud platform for AI-powered applications. In this role, you’ll work on backend services, distributed systems, and infrastructure that enable real-time data processing and intelligent decision-making at the edge.

You’ll collaborate closely with experienced engineers across platform, AI, and embedded systems, contributing to the design and implementation of scalable systems while growing your skills in edge computing and modern cloud infrastructure.

This is not a fully remote role -- you will be required to be onsite at least a few days per week!

Key Responsibilities:

• Design and implement platform software supporting AI workloads, edge inference, and distributed data pipelines across hybrid environments.
• Contribute to the architecture, design, and deployment of scalable systems in both cloud-based and on-premises runtime environments.
• Develop and maintain high-performance components in C/C++, Go, and Python, optimized for edge and real-time environments.
• Build and manage API-based middleware that connects AI models, data services, and frontend interfaces.
• Implement service-oriented architectures (SOA) and Software-as-a-Service (SaaS) frameworks to support modular, extensible system design.
• Leverage Infrastructure-as-Code (IaC) for automated provisioning, deployment, and configuration management.
• Employ containerization (Docker) and orchestration (Kubernetes) for edge-to-cloud deployments and lifecycle management.
• Integrate networking protocols (TCP/IP, for secure, high-throughput edge-cloud communication.
• Use CMake and BASH scripting for build automation, testing, and deployment pipelines.
• Collaborate using Git-based configuration management systems in a modern CI/CD environment.
• Work closely with data scientists and AI engineers to embed ML models into production-grade edge systems.
• Optimize performance, reliability, and scalability across resource-constrained and distributed computing environments.

Required Skills and Experience:

Candidates must be legally authorized to work in the United States without employer sponsorship and may be required to obtain and maintain a U.S. government security clearance in the future.

• 2-4 years of software engineering experience in embedded, cloud, or distributed systems.
• Proficiency and recent experience coding in C/C++ required .
• Strong knowledge of edge computing, AI platform development, or real-time data systems.
• Experience building backend systems or APIs
• Familiarity with cloud platforms (AWS, GCP, or Azure)
• Understanding of basic distributed systems concepts (e.g., scalability, latency, reliability)
• Ability to collaborate effectively and learn quickly in a fast-paced environment

Preferred Qualifications

• Experience with Go, and/or Python a plus.
• Experience with containers or Kubernetes
• Exposure to infrastructure-as-code or CI/CD pipelines
• Interest in AI/ML systems or model deployment
• Exposure to edge computing or real-time systems

Why Join Us

• Join a team that thrives on innovation and collaboration.
• Work on cutting-edge technology bridging embedded systems, cloud computing, and AI applications
• Collaborate with world-class engineers solving complex distributed systems challenges
• High ownership, fast iteration, and opportunities to lead architecture and innovation initiatives
• Competitive compensation, equity options, and a culture that values innovation and technical excellence.

Compensation range: $125,000 - $160,000. Actual position within the range will be determined based on experience level of the candidate.