Perception MLOps Infrastructure Engineer
Poway, CaliforniaOverview
General Atomics pioneers technologies with the potential to change the world. Behind a talented global team of engineers, GA delivers safe, sustainable, and economical solutions to meet growing global demands. Our Engineers have an opportunity to work on first of a kind product lines within an incredible, dynamic environment.
Engineering positions typically require a bachelor’s degree, master’s degree or PhD in engineering or a related technical discipline from an accredited institution and progressive engineering experience. Candidates from mechanical, electrical, and aerospace engineering backgrounds must know the fundamentals of engineering system developments, requirements, testing, and integration before getting to the final stages of customer interface and project management.
Schedule: Full-Time Salary
Job Level: Mid-Level (3-7 years)
Travel: 0 - 25
Success Profile
What makes a successful Perception MLOps Infrastructure Engineer at General Atomics? Check out the top traits we’re looking for and see if you have the right mix.
- Analytical
- Collaborative
- Inventive
- Problem Solver
- Team Player
- Creative
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 800-171 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 800-171, 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.
Salary:$81,080 - $141,650
Benefits
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Healthcare
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Pension, 401(k)/Retirement Plans
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Competitive Pay
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Multiple product lines means a variety of work
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Paid Time Off
“The company is growing, has a very good reputation and had open positions in my area of expertise (aircraft design/design methodology development).”– Peter, Senior Staff Engineer
“We don't ascribe to quotas; we do ascribe to securing the BEST talent to enrich our culture toward healthy diversification and active/viable community service. We are STEM advocates.”– Debra, CSSBB: Staff Engineer
“Every day is different, with different problems to solve and many programs to support. I am a problem solver and have always been motivated by the tough questions.”– Scott, Laser Scientist
“I work in the Components Engineering and Obsolescence Management Dept. Our efforts are saving General Atomics several millions of dollars by proactively leading and informing the company of all these decisions which significantly impact production, sustainment and new designs.”– John, Staff Engineer
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