Principal Wireless Systems Engineer

This role serves as the lead architect for the robot's communication system, responsible for the seamless movement of massive sensor datasets from edge nodes to our B200 inference cluster and other networking stacks. The engineer will own the entire communication stack, specifically solving the interference and "contention" challenges that arise when streaming high-bandwidth vision data and low-latency IMU telemetry over shared Wi-Fi and Bluetooth radios. They will optimize the Linux kernel and wireless drivers to ensure cross-country teleoperation feels instantaneous, maintaining a sub-150ms "glass-to-glass" latency even in RF-congested environments. This engineer will ensure that robotic foundation models receive high-fidelity, time-synced data without the jitter or packet loss typical of embedded wireless devices, enabling a robust cross-country teleoperation stack and the large-scale data collection required for model training.

• BS in Electrical Engineering, Computer Engineering, Computer Science, or a related field
• 10-15+ years of experience in embedded systems, with deep expertise at the intersection of wireless communication and real-time data processing
• Strong experience with Linux kernel internals (C/C++), including driver development (V4L2, IIO)
• Hands-on experience with high-performance networking techniques such as eBPF/XDP
• Deep understanding of wireless systems, including Wi-Fi/BT coexistence (PTA/WCI-2) and 802.11ax (Wi-Fi 6) optimization
• Experience building or optimizing low-latency streaming systems (e.g., WebRTC, SRTP)
• Familiarity with Modulation and Coding Scheme (MCS) tuning and RF performance optimization
• Experience working with RTOS and real-time system constraints
• Experience with high-speed interfaces (PCIe, SDIO, MIPI-CSI)
• Prior experience architecting communication systems for robotics, drones, or real-time vision systems

Nice to Haves

• MS or PhD in DSP, Wireless Communications, Control Systems, or related field
• Experience with hardware-specific optimization (e.g., Rockchip ISP/NPU, RKNN)
• Familiarity with hardware-accelerated video encoding (H.264/H.265)

Working Style

This is a high ownership, in person role based in San Francisco. We operate in a fast paced environment with long build cycles and tight iteration loops. Looking for individuals who are hands on, adaptable, and highly committed!

Efference builds an integrated perception and compute stack for robotics. We focus on highly synchronized, low-latency hardware and manufacturing at scale. Efference was founded by Gianluca Bencomo, a PhD student at Princeton University whose research spans visual neuroscience, Bayesian filtering for fast and robust sensor fusion, neural network inductive biases, and robotics perception. The company is backed by Y Combinator and Anti Fund.