MLOps Engineer: Build Scalable ML Pipelines & Platforms

UNAVAILABLE; McLean (VA); Sur place; USD 120 000 - 180 000; Plein temps

Résumé du poste

UNAVAILABLE in McLean, VA seeks an experienced MLOps Engineer to design, build, and operate scalable ML pipelines and production-grade systems. You will work with data scientists, data engineers, and cloud teams to streamline deployment, monitoring, and lifecycle management of ML models across client engagements.

The role emphasizes CI/CD for ML assets, secure deployment patterns, and collaboration to reduce technical debt while ensuring operational resilience and observability.

Qualifications

• Experience building end-to-end ML pipelines and production deployments.
• Strong Python and ML framework familiarity (scikit-learn, TensorFlow, PyTorch, XGBoost).
• Experience with cloud platforms (AWS/Azure/GCP) and ML services.
• Hands-on with CI/CD and containerization (Docker/Kubernetes).
• Familiarity with IaC tools and observability stacks.

Responsabilités

• Design, build, and support scalable ML pipelines and deployment workflows.
• Implement CI/CD for ML assets enabling testing, versioning, and promotion.
• Integrate models into production services via APIs and containers.
• Develop ML platform components: model registries, feature stores, lineage tools.
• Monitor performance and data drift; partner on retraining strategies.
• Collaborate with Data Engineers to ensure data quality for ML systems.
• Apply DevSecOps practices for secure deployment and compliance.
• Define ML ops standards and reusable patterns for teams.
• Troubleshoot pipeline and infrastructure issues and optimize performance.
• Stay updated on new MLOps tools and cloud-native ML tech.

Connaissances

Python

ML lifecycle management

DevOps

Cloud platforms

Observability

Collaboration

Formation

Bachelor's or Master's in CS/Data Engineering/ML/IS

Outils

Docker

Kubernetes

CI/CD tools

Terraform/CloudFormation

GitHub Actions/GitLab/Jenkins

Monitoring (Prometheus/Grafana/CloudWatch)

Description du poste

UNAVAILABLE in McLean, VA seeks an experienced MLOps Engineer to design, build, and operate scalable ML pipelines and production-grade systems. You will work with data scientists, data engineers, and cloud teams to streamline deployment, monitoring, and lifecycle management of ML models across client engagements.

The role emphasizes CI/CD for ML assets, secure deployment patterns, and collaboration to reduce technical debt while ensuring operational resilience and observability.