AI Platform Engineer

AI Platform Engineer (Junior Career)

The Lockheed Martin Artificial Intelligence Center (LAIC) team is seeking an experienced AI Platform Engineer to support enterprise Machine Learning and Artificial Intelligence systems. In this role, you will be creating products across the AI/ML lifecycle including development, deployment, and integration into other products. The selected candidate will focus on delivery of our core AI/ML platform offerings. Additionally, they will contribute to a broad range of projects across the enterprise to increase machine learning availability and value to Lockheed Martin.

The Selected Candidate Will

• Build and scale Kubernetes-based machine learning operations (MLOps) platforms and associated environments which enable thousands of engineers across LM and customer communities.
• Integrate machine learning libraries and operational frameworks into an end-to-end environment.
• Full-stack development and support of MLOps-centric software, integrating RESTful web-services.
• Work with AI/ML practitioners to solve complex problems and create unique solutions.
• Continuously evaluate the latest packages and frameworks.
• Create documentation and best practices to share with the AI/ML community.

What’s In It For You

From onsite to remote, we offer flexible work schedules to comprehensive benefits investing in your future and security. Learn more about Lockheed Martin’s comprehensive benefits package here.

Do you want to be part of a company culture that empowers employees to think big, lead with a growth mindset, and make the impossible a reality? We provide the resources and give you the flexibility to enable inspiration and focus - if you have the passion and courage to dream big, work hard, and have fun doing what you love then we want to build a better tomorrow with you. #LMLAIC

Basic Qualifications

• Bachelor’s Degree in Engineering, Computer Science, or other related discipline.
• Experience with Programming and Scripting, such as C++, Java, Python, Go, Bash.
• Experience with Pipeline Automation, such as ArgoCD, Tekton, GitLab CI/CD, Github Actions, Jenkins.
• Knowledge of DevSecOps and Cloud Native software development practices.
• Knowledge of common machine learning frameworks, such as TensorFlow, Torch, Sci-kit.

Desired Skills

• Experience with Containers, including Open Container Initiative (OCI) and Docker.
• Experience with Collaboration Tools, such as Slack/Teams, Confluence, GitLab.
• Experience with Kubernetes Package Management, such as Helm, Kustomize.
• Knowledge of Machine Learning Architectures, including GPU Computing, High Performance Computing (HPC).
• Knowledge of ML/AI orchestration, such as Kubeflow, Flyte, MLflow.
• Familiarity with Monitoring and Performance, such as Prometheus, Grafana, Dynatrace, Sysdig.
• Familiarity with public cloud computing services, such as AWS, GCP, Azure.
• Strong oral and written communication skills, and ability to collaborate with cross-functional partners.
• Creative and resourceful when it comes to problem-solving.
• A passionate can-do attitude. You are not afraid to try, learn, and improve.
• Self-motivated, self-directed, and the ability to thrive in a fast-paced environment in an industry that constantly changes.
• Empathy for teammates/users and a desire to make their work frictionless and more efficient.
• Passion for building things that are useful.

Other Important Information

By applying to this job, you are expressing interest in this position and could be considered for other career opportunities where similar skills and requirements have been identified as a match. Should this match be identified you may be contacted for this and future openings.

Key skills/competency

• AI Platform Engineer
• Machine Learning Operations (MLOps)
• Kubernetes
• Python
• DevSecOps
• Cloud Native
• CI/CD
• TensorFlow
• Docker
• Problem-solving