Cellular Systems Engineer

Autonomous Vehicle Fleet Engineer

We are developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of artificial intelligence, robotics, and design, we aim to provide the next generation of mobility-as-a-service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.

• B.Eng/M.S. in Electrical Engineering, Telecommunications, or a related field
• Expert-level knowledge of 4G-LTE and 5G- interfaces, specifically L1-L3 (PHY, MAC, RLC, PDCP, RRC, and NAS).
• Familiarity with IEEE 802.11 (a/b/g/n/ac/6/6E/7) protocols and TCP/IP networking.
• Deep, hands-on experience with modem-level chipset tools (e.g., Qualcomm QXDM/QCAT, Samsung ShannonDM, Wireshark).
• Proven track record of troubleshooting complex end-to-end live network performance issues, including mobility management, interference analysis, and call drop etc.
• Strong proficiency in Python is required for automation tools development and log analysis; other scripting languages are optional.
• Familiarity with RAN and Core Network architecture; ability to see beyond the log and understand how end-to-end components impact the system performance.
• 3–5 years of professional experience specifically in the cellular protocol domain.
• Prior work experience at client or in client's Industry

Applicants must be able to work directly for Artech on W2

• Work closely with field deployment optimization teams across connectivity system, firmware, and software engineer teams to identify, record, process, and interpret key device and service performance attributes.
• Act as the primary technical expert for analyzing modem-level field logs from chipsets such as Qualcomm (QXDM) and Samsung (Shannon), leading the development of programmatic tools to identify root causes for throughput drops, handover failures, Radio Link Failure, and connectivity instabilities.
• Develop end-to-end automation tools required to facilitate the identification and processing of these attributes at scale.
• Interpret key device and service performance attributes (KPIs) and recommend reconfigurations or architectural tweaks to the design process to improve e2e QoS.
• Work closely with system architecture and engineers to deliver system architecture, requirements, design, and prototype in the connectivity domain (4G-LTE, 5G , WiFi/GPS) to meet end-to-end quality-of-service of the autonomous driving use case requirements.