Lead Autonomy Software Engineer - MAGE

The Lead Autonomy Engineer is a key technical contributor and small engineering team lead on multiple programs aligned with division and/or group objectives. Mission autonomy is the ability for autonomous agents or teams to conduct strategic decision-making and coordinated actions toward longer-term operational objectives through persistent world modeling, predictive simulation, and adaptive planning under uncertainty and adversarial conditions. Essential Functions Lead a team to develop innovative solutions to address technical challenges derived from customer requirements. Serve as a subject matter expert in emerging mission autonomy technologies. Support or lead marketing and proposal efforts in mission autonomy. Support or lead managing and tasking team to achieve program milestones. Take primary responsibility for prime and customer-facing interactions. Stay current with industry trends, emerging technologies, and best practices in mission autonomy and other areas relevant to Scientific Systems. Collaborate with multi-disciplinary teams to advance R&D roadmaps. The role does require the ability to sit or stand at a desk and work on a computer for prolonged periods of time. This role may require occasional travel when necessary. May require the ability to push/pull/lift up to 15 pounds. Must be able to obtain and maintain a US DOD Security Clearance. Basic Qualifications: Bachelor of Science degree in Math, Statistics, Computer Science, Engineering, Physical Science, Operations Research, Data Science, or equivalent experienceand 7+ years of progressive autonomy technologies experience including team leadership in a related industry, a Master degree and 5+ years of related engineering experience, or a Ph.D. degree and 2+ years working in a related engineering role. Experience working in a team leadership role in a related industry. Proven track record of leading proposals and winning contracts. Proven track record of leading programs in the principal investigator role or similar experience. Experience in building and integrating software for edge platforms. Experience with C/C++, Python, and/or project-specific required languages. (e.g. Java, Rust, etc.) Experience assisting with non-technical programmatic priorities as needed, including staff planning, budget estimation and tracking, and customer-facing interactions. Background in robotics technologies related to motion planning, behavior modeling, or decision-making and their accompanying algorithms. Experience with simulation tools and environments (e.g., AFSIM, NGTS) for validation, verification, and training. Preferred Qualifications M.S. or Ph.D. degrees Familiar with AI/ML standard libraries and tools. Experience working in Linux-based development environments. Excellent organizational skills and attention to detail. Experience working on both classical autonomy and machine learning and the combination of the two, blending rule-based systems with learning-based methods such as reinforcement learning and generative methods to achieve resilient, adaptive behavior. Experience developing software modules that combine planning, decision-making, and behavior execution in dynamic, adversarial environments. Experience implementing and testing behavior architectures such as multi-agent collaboration, target engagement, payload management, reconnaissance, and engagement in adversarial scenarios. Ability to analyze mission logs to diagnose failures and optimize models for iterative development. Excellent oral and written communication skills including technical writing skills. Ability to identify and creatively solve complex problems Salary: $150,000 - $196,000 (Depends on Experience) Health Care Plan (Medical, Dental & Vision) Retirement Plan (401k, IRA) Life Insurance (Basic, Voluntary & AD&D) Paid Time Off (Vacation, Sick & Public Holidays) Family Leave (Maternity, Paternity) Short Term & Long Term Disability Training & Development Hybrid Work Schedule Free Food & Snacks Wellness Resources Summer 9/80 work schedule #J-18808-Ljbffr SSCI