Lockheed Martin is seeking to enhance and scale enterprise Machine Learning and Artificial Intelligence systems through the development and integration of a core AI/ML platform to increase machine learning availability and value across the company.
Requirements
- Experience with Containers, including Open Container Initiative (OCI) and Docker
- 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
Responsibilities
- 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
Other
- 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
