Serving Maryland and the Greater Washington D.C. area, SageCor Solutions (SageCor) is a growing company bringing complete engineering services and true full lifecycle System Engineering services to areas requiring (or desiring) nationally-recognized expertise in high performance computing, large data analytics and cutting edge information technologies.
Active TS/SCI W/ Polygraph Required.
SWE-3 Qualifications : Master's degree in Computer Science or related discipline from an accredited college or university, plus five (5) years of experience as a SWE, in programs and contracts of similar scope, type, and complexity.
OR
Bachelor's degree in Computer Science or related discipline from an accredited college or university, plus seven (7) years of experience as a SWE, in programs and contracts of similar scope, type, and complexity.
OR
Nine (9) years of experience as a SWE, in programs and contracts of similar scope, type, and complexity.
Position Description
The Software Engineer shall be responsible for designing, developing, and sustaining pipelines that enable machine-learning model training as well as large scale inference in a Kubernetes-based environment. The Software Engineer’s tasking shall include the following:
- Development of data-aware model training pipelines to facilitate unique customer requirements surrounding model provenance.
- Development of scalable, Kubernetes-based inference pipelines that compliantly handle in-flight data.
- Configuring and maintaining custom metrics to enable tuning of running pipelines.
- Experience using the Linux CLI.
- Experience developing with Python.
- Experience leveraging distributed processing solutions such as Spark and/or Dask for data processing workflows and ETL solutions.
- Experience developing and deploying containerized applications.
- Experience writing and deploying Kubernetes resources.
- Experience writing and deploying Helm charts.
- Experience developing with Go.
- Experience with CI/CD concepts & implementations (Gitlab, Flux CD, etc).
- Experience working with, and debugging, GPU-enabled applications.
- Experience with Policy Management Tools such as Kyverno.
- Experience using Imagine Builder Tools for Go such as Ko.
- Experience using a machine-learning framework (PyTorch, TensorFlow, etc).
- Experience with other ML pipelines/frameworks like KubeFlow, NeMo, PyTorch Lightning.
- Experience with metrics and monitoring tools such as Prometheus and Grafana.
- Experience with the Atlassian suite of tools.