FWDthink ยท 12 hours ago
Sr. MLOps Engineer, DHS Public Trust, Remote
Springfield, VA
Full-time
Remote
Senior Level
$150K/yr - $200K/yr
5+ years exp
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Responsibilities
Design, implement, and manage end-to-end ML pipelines, covering all stages from data ingestion and preprocessing to model training, evaluation, deployment, and monitoring.
Utilize tools like Apache Airflow , Kubeflow , MLflow , or TensorFlow Extended (TFX) for pipeline orchestration and automation.
Build scalable solutions using cloud platforms such as AWS SageMaker , Azure ML , or other government-approved environments, with a focus on distributed training and fault-tolerant systems.
Ensure robust testing processes and integration of CI/CD workflows to maintain pipeline reliability and performance.
Develop and maintain automated CI/CD pipelines for ML model deployment, leveraging tools like Jenkins , GitHub Actions , Azure Pipelines , or AWS CodePipeline .
Ensure efficient workflows through containerization ( Docker ) and version control systems like DVC or Git to manage models and code.
Collaborate with cross-functional teams to streamline iterative deployment processes, reduce downtime, and implement automated rollback mechanisms for failed deployments.
Monitor deployed models using tools like Prometheus , Grafana , or cloud-native solutions such as SageMaker Model Monitor or Azure Monitor .
Implement performance tracking metrics (e.g., precision, recall, F1 score, latency) and design strategies for detecting drift or underperformance in live environments.
Develop automated retraining pipelines and workflows to ensure continuous improvement and compliance with evolving requirements.
Archive and document model iterations for auditability and lifecycle transparency in accordance with government standards.
Qualification
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Required
ACTIVE DHS PUBLIC TRUST CLEARANCE
5+ years in MLOps, with a proven track record of deploying and managing production-grade ML systems.
Proficient in orchestration and automation tools (Airflow, Kubeflow, MLflow, or TFX).
Strong programming skills in Python, Bash, or other relevant languages.
Expertise in cloud platforms (AWS, Azure, or Google Cloud) and container technologies (Docker, Kubernetes).
Familiarity with monitoring tools and drift detection methodologies.
Exceptional problem-solving abilities, attention to detail, and the capacity to work effectively in a cross-disciplinary team.
Preferred
Experience with government contracting requirements or secure ML environments.
Knowledge of advanced drift detection and model retraining methodologies.
Certifications in cloud services (e.g., AWS Certified Machine Learning Specialty, Azure AI Engineer Associate).
Benefits
Competitive compensation
Company
FWDthink
FWDthink is an information technology services firm that helps Government agencies and Fortune 100 companies implement technological solutions, expand revenue or ROI and train our their personnel to sustain a new level of transformational growth.
11-50 employees
Funding
Current Stage
Early StageLeadership Team
Rabiah Sutton
CEO and BOLD thinker
Greg Sadler
Steady thinker [chief security officer]
Company data provided by crunchbase
