Autonomy AI/ML Software Engineer - Onsite

Job Description Joining Collins Aerospace isn't just about finding a job; it's about embarking on a journey to redefine the future of aerospace technology. Collins Aerospace, an RTX company, is a leader in technologically advanced and intelligent solutions for the global aerospace and defense industry. Collins Aerospace has the capabilities, comprehensive portfolio, and expertise to solve customers' toughest challenges and to meet the demands of a rapidly evolving global market. We are seeking a forward‑leaning AI/ML Software Engineer to advance next‑generation Command and Control and Autonomy capabilities for the Connected Battlespace. In this role, you will design and implement distributed reasoning, multi‑agent coordination, and mission‑adaptive autonomy technologies that operate across cooperative, competitive, and adversarial environments. You will architect intelligent, resilient, edge‑deployed AI systems that support both near‑term mission insertion and future-state capability development. This position sits within Defense Technology's Applied Research and Technology organization, partnering across Collins to define and deliver breakthrough autonomy, explainable AI, and decentralized C2 solutions.

Onsite:

This is an onsite role supporting our Cedar Rapids, IA location.

What You Will Do:

Develop multi‑agent coordination algorithms and distributed C2 autonomy behaviors Apply reinforcement learning to resource allocation, tasking, and cooperative/adversarial scenarios Design intent‑driven autonomy functions that translate commander intent into executable behaviors Implement multimodal human‑machine interaction capabilities and operator‑centric mission tools Engineer probabilistic reasoning, adaptive learning, and intelligent data‑management components for DDIL environments Build and integrate distributed AI agents into simulation, laboratory, and operationally representative test environments Develop scalable autonomy and AI architectures spanning edge nodes, federated systems, and cloud environments Implement and maintain MLOps pipelines for continuous model refinement, evaluation, and deployment Ensure interoperability with open standards, cyber‑secure interfaces, and multi‑domain system requirements Transition advanced autonomy concepts into operational prototypes and mission systems

Qualifications You Must Have:

Typically requires a University Degree or equivalent experience and minimum 8 years prior relevant experience, or An Advanced Degree in a related field and minimum 5 years experience. Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Systems Engineering, Robotics, Applied Mathematics, or related field 5+ years of experience in AI/ML, autonomy, distributed systems, or advanced C2 architectures Strong background in probabilistic reasoning, reinforcement learning, or multi‑agent systems Experience building resilient distributed computing or edge‑deployed systems Proficiency in Python and at least one systems language such as C++, Rust, or Go Experience developing and deploying ML models using frameworks such as PyTorch or TensorFlow Familiarity with autonomy or distributed‑system frameworks such as ROS/ROS2, messaging/streaming platforms, or agent‑based environments Experience deploying AI technologies into operational or near‑operational environments Experience with autonomy evaluation, simulation‑based testing, or mission analytics U.S. Citizen - U.S. citizenship is required, as only U.S. citizens are authorized to access information under this program/contract U.S. citizenship and the ability to obtain and maintain a U.S. Government Security Clearance (Secret) on Day 1 of employment.

Qualifications We Prefer:

Experience implementing explainable AI, safety‑constrained autonomy, or reasoning guardrails Background in human‑machine teaming, operator‑centric autonomy, or cognitive‑aware interfaces Experience developing AI or autonomy systems for contested, DDIL, or bandwidth‑limited environments Familiarity with Neurosymbolic AI, hybrid reasoning architectures, or distributed Bayesian inference Experience with multi‑agent coordination, distributed optimization, or Value‑of‑Information‑driven algorithms Integration experience with edge‑to‑cloud distributed autonomy architectures Experience supporting advanced research programs, IRAD strategy, or technology transition planning Demonstrated ability to guide technical approach, architectural direction, or cross‑team autonomy strategy

What We Offer:

Medical, dental, and vision insurance Three weeks of vacation for newly hired employees Generous 401(k) plan that includes employer matching funds and separate employer retirement contribution, including a Lifetime Income Strategy option Tuition reimbursement program Student Loan Repayment Program Life insurance and disability coverage Optional coverages you can buy: pet insurance, home and auto insurance, additional life and accident insurance, critical illness insurance, group legal, ID theft protection Birth, adoption, parental leave benefits Ovia Health, fertility, and family planning Adoption Assistance Autism Benefit Employee Assistance Plan, including up to 10 free counseling sessions Healthy You Incentives, wellness rewards program Doctor on Demand, virtual doctor visits Bright Horizons, child and elder care services Teladoc Medical Experts, second opinion program And more! Your Responsibilities Develop multi‑agent coordination algorithms and distributed C2 autonomy behaviors Apply reinforcement learning to resource allocation, tasking, and cooperative/adversarial scenarios Design intent‑driven autonomy functions that translate commander intent into executable behaviors Implement multimodal human‑machine interaction capabilities and operator‑centric mission tools Engineer probabilistic reasoning, adaptive learning, and intelligent data‑management components for DDIL environments Build and integrate distributed AI agents into simulation, laboratory, and operationally representative test environments Develop scalable autonomy and AI architectures spanning edge nodes, federated systems, and cloud environments Implement and maintain MLOps pipelines for continuous model refinement, evaluation, and deployment Ensure interoperability with open standards, cyber‑secure interfaces, and multi‑domain system requirements Transition advanced autonomy concepts into operational prototypes and mission systems Job Details Function Corporate Sub-Function IT, Software & Data Science Work Type onsite Contract Full-Time Location Cedar Rapids, United States Job

ID IGQ97B

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