Network Software Engineer, Real-Time Systems

Job description

We’re looking for a Software Engineer to build the connectivity layer powering FieldAI’s robotic platforms in the real world.

In this role, you’ll design and deploy low-latency, high-reliability communication systems that enable seamless, real-time interaction between robots and remote operators. You’ll work across cellular networks (4G/5G), edge-to-cloud systems, and distributed device infrastructure to ensure robust performance in dynamic, unpredictable environments.

You’ll tackle hard problems like network handoffs, intermittent connectivity, and maintaining real-time performance under mobility, interference, and degraded conditions. This includes building systems that gracefully adapt to changing network quality while preserving responsiveness and reliability.

This is a deeply hands-on role at the intersection of robotics, networking, and distributed systems. Your work will directly determine how our robots perceive, communicate, and operate in the field.

Job responsibilities

Build low-latency, bidirectional audio/video streaming systems for telepresence and teleoperation
Design and optimize real-time communication over private 5G and heterogeneous networks
Monitor and improve network performance (latency, jitter, packet loss, throughput) in dynamic environments
Implement QoS strategies, congestion control, and adaptive streaming for reliable operation
Develop, test, and deploy communication systems directly on robotic platforms
Ensure robust performance under mobility, degraded connectivity, and real-world conditions

Job requirements

MS or PhD in Computer Science, Robotics, Electrical Engineering, or a related field
Strong experience building real-time or near real-time communication systems (e.g., TCP/UDP, RTP/RTCP, WebRTC)
Solid understanding of networking fundamentals, especially in wireless and cellular contexts (latency, jitter, handoffs, bandwidth constraints)
Experience working with Linux networking and debugging tools (e.g., tcpdump, iperf, ss, iw)
Familiarity with distributed systems and device-to-cloud communication architectures
Experience developing and validating systems on physical hardware, not just simulations
Working knowledge of ROS/ROS2 or similar frameworks for distributed robotic systems
Experience deploying systems over cellular networks (LTE/5G), including private 5G setups
Background in telepresence, teleoperation, or real-time audio/video streaming systems
Deep understanding of adaptive bitrate, congestion control, QoS, and fault-tolerant networking
Experience with media and streaming frameworks (e.g., WebRTC, GStreamer, RTP pipelines)
Familiarity with mesh networking or device-to-device communication systems
Experience designing systems that gracefully handle intermittent connectivity and mobility
Strong ownership mindset, from system design through real-world deployment and iteration

Apply on Field AI website Save

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