What are the responsibilities and job description for the Software Engineer – AI Platforms & Edge Computing position at MatrixSpace?
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 are seeking a Software Engineer with 2-4 years of industry experience and proven expertise in C/C , Go, and Python to join our core engineering team. This role focuses on building and scaling AI-driven platforms that operate across edge computing environments and cloud infrastructures.
You will support the design, implementation, and operation of our Platform Software, enabling high-performance data processing, AI inference, and real-time communication across distributed edge and cloud systems. The ideal candidate thrives in a startup environment, combining technical proficiency with a growth mindset and system-level thinking.
Key Responsibilities
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.
We are seeking a Software Engineer with 2-4 years of industry experience and proven expertise in C/C , Go, and Python to join our core engineering team. This role focuses on building and scaling AI-driven platforms that operate across edge computing environments and cloud infrastructures.
You will support the design, implementation, and operation of our Platform Software, enabling high-performance data processing, AI inference, and real-time communication across distributed edge and cloud systems. The ideal candidate thrives in a startup environment, combining technical proficiency with a growth mindset and system-level thinking.
Key Responsibilities
- Design and implement platform software supporting AI workloads, edge inference, and distributed data pipelines across hybrid environments.
- Lead 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, HTTPS) 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.
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 in C/C , Go, and/or Python.
- Strong knowledge of edge computing, AI platform development, or real-time data systems.
- Understanding of TCP/IP and HTTPS for reliable and secure communication layers.
- Proven experience with service-oriented architectures, Infrastructure-as-Code frameworks (Terraform, CloudFormation), and SaaS systems.
- Hands-on experience with Docker, Kubernetes, and cloud-native deployment.
- Familiarity withCMake, BASH, and Linux-based build environments.
- Experience using Git or similar configuration management systems in collaborative software development.
- Exposure to AWS or other public cloud environments (Azure, GCP).
- Strong debugging, profiling, and performance optimization skills in distributed runtime environments.
- Experience building edge AI platforms, including model serving, data orchestration, or sensor-to-cloud integrations.
- Familiarity with AI/ML deployment frameworks (e.g.,TensorRT, ONNX Runtime,TorchServe).
- Understanding ofreal-time systems, streaming data, or event-driven architectures.
- Working experience in databased such as Postgres and Redis
- Experience with DevOps, CI/CD, and observability tools (Prometheus, Grafana).
- Knowledge of security, identity, and network optimization in edge environments.
- 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.
Salary : $150,000 - $170,000