Senior ML Ops/AI Ops Engineer
The Aerospace Corporation2 days ago
El Segundo, CA, USASenior / Staff+
Base Salary
$107k - $203k/yr
Responsibilities
- Define, design, implement, and operate an MLOps platform and framework.
- Build and maintain CI/CD/CT pipelines for model training, validation, deployment, and retraining.
- Deploy ML models using Docker, Kubernetes, and model-serving frameworks.
- Maintain experiment tracking, model versioning, reproducibility, feature stores, model registries, lineage tracking, and audit trails.
- Automate provisioning of ML compute, storage, and GPU infrastructure across cloud environments.
- Monitor model performance, data drift, concept drift, and prediction quality and trigger alerts or retraining when needed.
- Manage GPU and TPU resources for distributed training and high-throughput inference while optimizing cost and performance.
- Partner with Data Engineering to support reliable and governed data pipelines for training and inference.
- Collaborate with data scientists, ML engineers, and Platform/DevOps teams to productionize experimental models.
- Diagnose and resolve production issues involving model latency, throughput, resource contention, and pipeline failures.
Requirements
- Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
- At least 3 years of experience in MLOps, ML Engineering, DevOps, or a closely related role with direct experience deploying ML models to production.
- Staff IV consideration requires at least 5 years of relevant experience.
- Proficiency in Python and strong software engineering fundamentals, including testing, version control, and code review.
- Hands-on experience with Docker and Kubernetes for ML workloads.
- Experience with at least one major cloud platform and its ML or compute services, including AWS, Azure, or GCP.
- Familiarity with Jenkins, ArgoCD, GitHub Actions, or GitLab CI for ML pipelines.
- Experience with MLflow, DVC, or similar experiment tracking and model versioning tools.
- Understanding of ML training and inference lifecycles, model evaluation metrics, and data drift.
- Experience working within Agile development processes and resolving software and system issues.
- Ability to build effective relationships, drive consensus, and collaborate with peers and customers.
- Ability to obtain and maintain a DoD SECRET clearance; U.S. citizenship is required for clearance eligibility.
- Preferred qualifications include a master's degree, experience with managed ML platforms, large language model deployment and scaling, MLOps frameworks, GPU cluster management, and AIOps or anomaly-detection platforms.
Benefits
- Competitive compensation based on performance and value delivered.
- Comprehensive health care and wellness plans.
- Paid holidays, sick time, vacation, and standard or alternate work schedules.
- Telework options are available, although this role requires full-time on-site work at the El Segundo, California facility.
- 401(k) plan with company-paid contributions of 8%, 10%, or 12% based on years of service, plus matching contributions; employees are immediately eligible and vested.
- Flexible spending accounts and a variable pay program for exceptional contributions.
- Relocation assistance.
- Professional growth, development, and education assistance programs.
- Inclusive work environment focused on teamwork, flexibility, and respect.
Tech Stack
AWSAzureDockerDVCGitHub ActionsGitLab CI/CDGoogle Cloud PlatformJenkinsKubernetesMLflowPythonTerraform
Categories
About The Aerospace Corporation
The Aerospace Corporation is a nonprofit operator of a federally funded research and development center, providing independent systems engineering, research, and mission assurance for U.S. government space programs. It supports defense, civil, and some commercial customers across satellites, launch vehicles, ground systems, remote sensing, and cyber. Founded in 1960 and headquartered in Chantilly, Virginia, it advises on acquisition, design, testing, and operations to improve reliability of national security space systems.