Perception MLOps Infrastructure Engineer

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.

The Perception Infrastructure Engineer designs, builds, and maintains the compute, data, and CI/CD infrastructure that enables the development, test, and deployment of advanced perception algorithms for multi-sensor systems.

This role bridges DevOps, software engineering, and systems integration to ensure scalable, reproducible environments for radar, EO/IR, and fused-sensor perception workloads executed on GPU-based platforms across simulation, lab, and flight environments.

DUTIES AND RESPONSIBILITIES:

• Architect, deploy, and maintain on-prem and isolated network compute infrastructure supporting perception algorithm development and test (GPU servers, storage arrays, and networked development hosts).
• Design and manage GitLab CI/CD pipelines for build, test, and container deployment of perception software baselines (C++, CUDA, Python, ROS2).
• Support algorithm developers with containerized and reproducible environments for ML training, sensor simulation, and embedded inference (Docker, Podman, Singularity).
• Implement and maintain infrastructure-as-code for provisioning and configuration management (Ansible, Terraform, or equivalent).
• Manage integration of data management tools (DVC, MLflow, Git LFS) for large datasets, model artifacts, and version tracking.
• Ensure secure network configuration and compliance with NIST SP and corporate cybersecurity controls.
• Optimize GPU cluster scheduling and resource utilization (e.g., Slurm, Kubernetes, or GitLab runners for H100-class nodes).
• Collaborate closely with perception algorithm engineers, autonomy software leads, and IT security to deliver reliable, high-throughput development pipelines.
• Support integration and test of perception software in hardware-in-the-loop and flight test environments

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 engineering experience as follows; five or more years of experience with a bachelors degree or three or more years of experience with a masters degree. May substitute equivalent machine learning engineer experience in lieu of education.
• Proficiency with Linux system administration, networking, and shell scripting.
• Experience with GitLab CI/CD or comparable build automation systems.
• Strong working knowledge of containerization (Docker/Podman) and environment reproducibility for development and deployment.
• Familiarity with GPU compute environments (CUDA drivers, Slurm scheduling, NVIDIA management tools).
• Demonstrated experience maintaining source control and artifact management systems (Git, DVC, Artifactory).
• Excellent documentation and troubleshooting skills across heterogeneous systems.

• Desired Qualifications

• Experience supporting AI/ML or perception pipelines for radar, EO/IR, or autonomy applications.

• Familiarity with C++, Python, and CUDA build environments.
• Experience in air-gapped or classified network environments.
• Knowledge of Kubernetes, MLflow, or Prometheus/Grafana monitoring.
• Understanding of DoD cybersecurity frameworks (RMF, NIST , STIG compliance).

• Prior experience in aerospace, defense, or autonomy systems integration.

• Soft Skills and Team Fit

• Highly collaborative — able to work alongside algorithm developers, autonomy engineers, and IT security.

• Comfortable with rapid iteration, cross-functional coordination, and ownership of the end-to-end perception software lifecycle.

• System thinker with a bias for automation, reproducibility, and mission readiness.

• Ability to obtain and maintain a DOD security clearance required.

Job Type: Full-Time Salary

Salary range: 81, ,650