Full Job Description
Responsibilities
Design and build task environments across wireline networking, radio access, and non-terrestrial networks
• Write deterministic verifiers. Sources include network simulators, formal checkers such as Batfish or YANG validation, and closed-form physics such as orbit propagation and link budgets
• Impose action budgets and hidden state so that exhaustive search does not work and the task measures diagnostic policy rather than brute force
• Define invariants, and make any repair that breaks a previously satisfied property fail the episode
• Calibrate difficulty by running frontier models against each task, then analyze failures to confirm they come from domain reasoning rather than ambiguity or broken grading
• Work with research partners inside and outside the team to turn measured capability gaps into published findings
Minimum Qualifications
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Bachelor's degree in electrical engineering, computer science, or a related field, plus five years of relevant experience
• Production experience in at least one of: network operations and configuration, radio access systems, or satellite and aerial communications
• Proficiency in Python, with experience building and maintaining production or research codebases, and comfort building and debugging simulation or emulation environments
• Experience writing automated verification or test infrastructure where correctness is checked by a program, not by inspection
• Able to reason about a system from partial telemetry and explain why one hypothesis fits the evidence better than another
Preferred Qualifications
• Experience in adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Experience in programming languages such as C, C++, or Java, and scripting languages such as Python, Javascript, or PHP
• Experience improving quality through thoughtful code reviews, appropriate testing, proper rollout, monitoring, and proactive changes
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• 6+ years of experience in a relevant domain or 4+ years of experience with a Ph.D
