Machine Learning Engineer IV

Job Summary

General Atomics Aeronautical Systems, Inc. (GA-ASI), an affiliate of General Atomics, is a world leader in proven, reliable remotely piloted aircraft and tactical reconnaissance radars, as well as advanced high-resolution surveillance systems.

DUTIES AND RESPONSIBILITIES:
With consultative direction, this position leads the architecture, integration, and deployment of intelligent autonomous systems across defense and aerospace platforms. The role combines deep expertise in AI/ML, embedded software, and real-time computing with business acumen and mission-driven systems thinking. The successful candidate will architect scalable autonomy solutions from edge to cloud, enabling next-generation unmanned systems, ISR platforms, and immersive command-and-control applications.

• Architect End-to-End Autonomous Systems
  Lead the design of advanced autonomy solutions across air, land, sea, and space domains, integrating real-time decision-making, sensor fusion, and AI/ML models into mission-critical embedded platforms.
• Deliver Embedded AI at the Tactical Edge
  Develop and optimize AI/ML models for inference on SWaP-constrained systems using accelerators such as Intel Gaudi, Habana Greco/Goya, and custom ASICs. Support use cases like UAV swarm coordination, target tracking, and autonomous navigation.
• Integrate Cloud-Enabled C2 & Simulation Systems
  Deploy cloud-scale training/inference infrastructure for simulation, digital twin, and real-time decision support systems using Kubernetes, OpenShift AI, and high-performance compute clusters.
• Support Classified and Dual-Use Applications
  Ensure autonomy systems meet cybersecurity, export control, and operational security requirements in both classified and dual-use defense environments.
• Lead Customer-Focused Prototyping & Innovation
  Collaborate directly with DoD, IC, and Tier-1 aerospace partners to co-develop prototype solutions aligned with mission profiles, platform constraints, and acquisition pathways.
• Build and Scale Ecosystem Enablement Tools
  Deliver SDKs, technical documentation, GitHub examples, and tutorials to accelerate adoption and developer onboarding across defense integrators and mission engineering teams.
• Drive Strategic Business Development
  Engage with defense primes, government agencies, and mission owners to shape AI autonomy roadmaps, win new programs, and execute joint development agreements for cutting-edge autonomous platforms.
• Champion AI Technical Leadership in the Defense Sector
  Represent the organization at technical interchange meetings, customer summits, and defense symposia, shaping how autonomy is deployed at scale in operational theaters.
• Ensure Mission Assurance and Compliance
  Architect systems to meet MIL-STD, DO-178C, and cybersecurity compliance (e.g., RMF, STIGs), supporting accreditation and fielding in secure environments.
• Other duties as assigned or required

We recognize and appreciate the value and contributions of individuals with diverse backgrounds and experiences and welcome all qualified individuals to apply.

Job Qualifications

• Typically requires a bachelors masters degree or PhD in computer science, engineering, mathematics, or a related technical discipline from an accredited institution and progressive machine learning experience as follows; nine or more years of experience with a bachelors degree, seven or more years of experience with a masters degree, or four or more years with a PhD. May substitute equivalent machine learning engineer experience in lieu of education.
• Expert understanding of autonomous systems which includes the software stack, architecture, design, algorithms, testing and verification
• Expert knowledge of C++ used in autonomous systems
• Expert knowledge of DevSecOps practices
• Experience in developing fully autonomous systems, software stacks, deployments in real world applications. (ADAS, Drones, Robotics, Etc. preferred)
• Experience in developing and leading scalable software architectures from scratch.
• Experience in development and deploying Machine Learning/Deep Learning solutions.
• Have a track record in being a change agent to drive autonomy solutions in the one or more industries.
• Understanding and continuous learning of industry regulations and standards
• Experience in optimizing AI models to meet edge processing requirements.
• Technical expertise in the application of engineering principles, concepts, theory, and practice as well as project management and leadership skills including organizing, planning, scheduling, and coordinating workloads to meet established deadlines or milestones.
• Strong communication, leadership, presentation, and interpersonal skills are required to enable an effective interface with other departments, all levels of management, professional and support staff, customers, potential customers, and government representatives
• Excellent verbal and written communication skills.
• Ability to obtain and maintain a DoD security clearance is required.

Preferred Qualifications

• MS or PhD in Electrical Engineering, Computer Science, Robotics, or related field; MBA or defense acquisition training a plus.
• 14+ years of experience delivering autonomous or AI-enabled systems, including fielded capabilities in defense or aerospace platforms.
• Deep technical background in embedded AI, computer vision, perception, and decision systems for autonomous platforms.
• Experience working with U.S. DoD programs, FFRDCs, or Tier-1 defense contractors on autonomy-related initiatives.
• Familiarity with defense-relevant frameworks: MOSA, FACE, SOSA, and compliance standards (e.g., NIST 800-53, FIPS, STIGs).
• Proven success in technical business development and joint solutioning with government and defense industry partners.
• TS/SCI clearance or ability to obtain one strongly preferred.