Derq is an MIT spinoff building AI-powered traffic safety and smart infrastructure.
We’re a team of passionate innovators, leveraging the latest in AI and technology to transform the future of mobility.
Our platform enhances road safety and traffic management by turning real-time data into actionable insights for cities and road operators.
Our patented technology collects and analyzes data from connected sensors like cameras, radar, and traffic signal controllers to help predict and prevent road incidents.
We deploy edge and cloud solutions that make intersections and highways safer and smarter.
Role Overview We’re looking for a Software Engineer to work on real-time, performance-critical systems powering traffic detection and smart mobility solutions.
You’ll focus on building and optimizing software that runs across edge devices and cloud systems, with strong exposure to low-latency processing, system performance, and hardware integration.
You will own and contribute to critical system components end-to-end, including system behavior in production—covering performance, reliability, observability, networking, and deployments.
This is primarily a real-time / edge systems role, with backend exposure and light frontend work for internal tools, dashboards, APIs, and system monitoring.
You’ll be working on live traffic deployments, where robustness, fault tolerance, and performance directly impact safety-critical infrastructure.
Key Responsibilities Design, develop, and maintain production-grade software systems across edge and cloud with a focus on performance, reliability, and low latency Build and optimize real-time data processing and inference pipelines, integrating ML models into production systems Implement features and enhancements within existing system architecture and design guidelines Profile, optimize, and debug system behavior across CPU, memory, I/O, networking, and distributed systems Troubleshoot and resolve complex production issues across application, OS, and network layers Support and optimize edge systems, including hardware–software integration with sensors, cameras, and traffic controllers Build and operate reliable edge coordination systems (e.
g., heartbeats, failover and recovery mechanisms) Design and maintain backend services, APIs, and internal tools for system operation and monitoring Improve system observability through logging, monitoring, diagnostics, and performance tracking Design and maintain networking components (e.
g., VPNs, proxies, routing, secure edge–cloud connectivity) Develop and maintain CI/CD pipelines for build, packaging, deployment, and rollback across edge and cloud environments Implement secure access control and system isolation mechanisms on Linux-based systems Collaborate with ML, QA, and deployment teams to integrate, test, and support systems in real-world deployments 3–5 years of experience in software engineering or a related field Strong experience in real-time systems, high-performance backend systems, or edge/embedded computing Proficient in C++ or Python (both is a strong plus) Solid understanding of Linux systems, multithreading, concurrency, and system performance optimization Experience debugging complex systems in production environments Experience with testing frameworks and CI/CD pipelines Working knowledge of networking fundamentals (TCP/IP, DNS, routing, basic VPN/proxy concepts) Exposure to hardware integration, sensors, or edge devices is a plus Familiarity with computer vision pipelines or ML systems is a plus
