Role OverviewWe are seeking an experienced MLOps Engineer to automate secure deployment, evaluation, monitoring, and lifecycle management for on-premises AI services for a Federal data analytics and AI modernization initiative.
What You Will Do
Design, develop, and maintain data pipelines and ETL/ELT workflows supporting machine learning, NLP, retrieval, and advanced analytics.
Why It Might Be a Fit
The team will deliver a secure, scalable platform that integrates structured and unstructured data, provides data visualization and traceable AI-assisted analytics, and gives examiners centralized tools for search, review, monitoring, and decision support.
Requirements
- Demonstrated experience building, integrating, and operating data pipelines for machine learning, NLP, information retrieval, or advanced analytics.
- Hands-on experience with feature engineering, document processing, embeddings, curated datasets, data transformation, and reproducible data workflows.
- Strong proficiency in Python and SQL for data engineering, data transformation, automation, and model-support workflows.
- Experience working with structured and unstructured data and preparing data for AI/ML or analytics applications.
- Experience implementing data quality controls, data validation, provenance, metadata, versioning, lineage, and source traceability for AI/ML or data-intensive systems.
- Experience troubleshooting and optimizing data pipelines, integrations, transformations, and data-processing workflows.
- Ability to develop clear technical documentation covering data pipelines, schemas, transformations, dependencies, and operational processes.
- Strong technical communication, problem-solving, and cross-functional collaboration skills.
- U.S. citizenship and ability to obtain and maintain Top Secret eligibility, as required for contractor personnel supporting the effort.
Benefits
- Competitive compensation
- Opportunities for bonuses
- Employer-paid health care
- Training and development funds
- 401k match
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