Software Engineer (AI Platforms & Edge Computing)

TL;DR

Software Engineer (AI Platforms & Edge Computing): Building and scaling AI-driven platforms that operate across edge computing environments and cloud infrastructures with an accent on high-performance data processing and real-time communication. Focus on designing distributed data pipelines, implementing service-oriented architectures, and embedding ML models into production-grade edge systems.

Location: Hybrid in Burlington, MA. Must be legally authorized to work in the United States without employer sponsorship.

Company

hirify.global builds technology bridging the physical and digital worlds by combining embedded systems, radar sensing, cloud computing, and AI.

What you will do

• Design and implement platform software for AI workloads and edge inference across hybrid environments.
• Develop high-performance components using C/C++, Go, and Python optimized for real-time environments.
• Build API-based middleware to connect AI models, data services, and frontend interfaces.
• Manage edge-to-cloud deployments using Docker, Kubernetes, and Infrastructure-as-Code (Terraform, CloudFormation).
• Collaborate with data scientists and AI engineers to embed ML models into production-grade edge systems.
• Optimize performance and scalability across resource-constrained distributed computing environments.

Requirements

• 2-4 years of software engineering experience in embedded, cloud, or distributed systems.
• Proficiency in C/C++, Go, and Python.
• Must be legally authorized to work in the US without employer sponsorship and be able to obtain a security clearance.
• Strong knowledge of edge computing, AI platform development, or real-time data systems.
• Experience with Docker, Kubernetes, and cloud-native deployment (AWS, Azure, or GCP).
• Familiarity with Linux-based build environments, CMake, and BASH scripting.

Nice to have

• Experience with AI/ML deployment frameworks such as TensorRT, ONNX Runtime, or TorchServe.
• Working experience with Postgres and Redis databases.
• Experience with DevOps, CI/CD, and observability tools like Prometheus and Grafana.
• Understanding of event-driven architectures and streaming data.

Culture & Benefits

• Work on cutting-edge technology bridging embedded systems and AI applications.
• High ownership and fast iteration within a startup environment.
• Collaborate with world-class engineers solving complex distributed systems challenges.
• Competitive compensation and equity options.