Principal Network Systems Researcher
The Principal Network Systems Researcher at STR's Intelligence Division will lead a team of engineers and scientists to develop advanced analytics and machine learning solutions addressing complex national security challenges. This role involves collaborating with experts in software engineering, algorithm development, and academia to create innovative systems that process diverse and unstructured data sources. STR, founded in 2010, specializes in applying technology to national security problems, delivering cybersecurity, distributed sensing, and AI solutions for defense, intelligence, and homeland security customers. (str.us)
In this position, the researcher will work closely with dedicated teams to develop and deliver novel software and hardware systems that span research, development, and deployable production systems. Responsibilities include understanding customer intent, efficiently decomposing tasks for team execution, and collaborating with technologists and business leaders within the organization for business development and capture. The role requires utilizing state-of-the-art deep learning methods and networking expertise to improve networked systems for real-life scenarios.
Candidates should possess a BS, MS, or PhD in Machine Learning, Computer Science, or a related Engineering discipline, with 12+ years of experience for a BS, 10+ years for an MS, or 5+ years for a PhD. Experience in using state-of-the-art machine learning to solve real-world problems across both resource-constrained edge and resource-rich network core environments is essential. A strong understanding of networking/communications theory per the OSI stack model and working knowledge of unsupervised and semi-supervised learning techniques are also required. Familiarity with software design patterns, version control (Git), and collaboration tools (JIRA, Confluence) is important.
The full-time salary range for this position is $230,000 - $280,000, based on external market data and factors such as the candidate’s experience, education, training, key skills, security clearances, and prevailing market and business conditions. STR offers a collaborative learning environment that supports deep technical understanding and recognizes the contributions and achievements of all team members. Employees are encouraged to push the envelope of technology and make the world safer through their work.
STR is committed to creating a collaborative learning environment that supports deep technical understanding and recognizes the contributions and achievements of all team members. The company emphasizes sustained technical innovation, drawing engineers and researchers who want to apply cutting-edge technology to problems with direct national security relevance. STR operates on a hybrid work model and places emphasis on sustained technical innovation, drawing engineers and researchers who want to apply cutting-edge technology to problems with direct national security relevance. (str.us)