MLOps Engineer

Steampunk • McLean, VA

1d • $115,000 - $150,000

About The Position

We are seeking a MLOps Engineer to design, build, and support the infrastructure, tooling, and automation that enable scalable and reliable machine learning systems across our client engagements. This role is responsible for operationalizing ML models, implementing robust pipelines, and ensuring smooth transitions from experimentation to production. The MLOps Engineer works closely with Data Scientists, AI Developers, Data Engineers, and cloud engineering teams to streamline model deployment, monitoring, and lifecycle management in alignment with mission needs. You will contribute to the growth of our AI & Data Exploitation Practice!

Requirements

• Ability to hold a position of public trust with the U.S. government.
• Bachelors or Master’s degree in Computer Science, Data Engineering, Machine Learning, Information Systems, or a related technical discipline.
• Masters Degree and 0 years of experience OR Bachelors Degree and 2 years of experience OR No degree and 6 years of experience.
• 2+ years of experience in MLOps, ML engineering, DevOps, cloud engineering, or applied ML development.
• Proficiency in Python and familiarity with ML frameworks such as scikit-learn, TensorFlow, PyTorch, or XGBoost.
• Hands-on experience with at least one cloud platform (AWS, Azure, or GCP) and associated ML/DevOps services (e.g., SageMaker, Azure ML, Vertex AI, EKS/AKS/GKE).
• Practical experience with CI/CD tools (GitHub Actions, GitLab CI, Jenkins) and containerization (Docker, Kubernetes).
• Strong understanding of ML lifecycle management, including versioning, packaging, deployment, monitoring, and retraining.
• Familiarity with infrastructure-as-code tools such as Terraform or CloudFormation.
• Experience with logging, observability, and monitoring frameworks (CloudWatch, Prometheus, Grafana, ELK stack, Datadog, etc.).
• Ability to collaborate with Data Scientists, Engineers, and mission stakeholders to ensure ML systems deliver operational value.
• Strong communication skills and the ability to document workflows, architecture decisions, and runbooks.

Nice To Haves

• AWS ML Specialty
• AWS DevOps Engineer
• Azure Data Scientist Associate
• Google Professional Machine Learning Engineer
• Databricks Machine Learning Associate/Professional

Responsibilities

• Develop and maintain end-to-end ML pipelines, including data ingestion, feature engineering, model training, model packaging, deployment, and monitoring workflows.
• Implement CI/CD pipelines for ML assets, enabling automated testing, versioning, promotion, and reproducibility across environments.
• Integrate ML models into production services using APIs, microservices, serverless functions, or container orchestration frameworks like Kubernetes.
• Build and manage core ML platform components such as model registries, experiment tracking systems, feature stores, datasets, job schedulers, and lineage tools.
• Monitor model performance, system health, and data drift using logging, observability frameworks, dashboards, and alerting systems; partner with Data Scientists to refine retraining strategies.
• Collaborate with Data Engineers to ensure data pipelines and data quality support high-performing ML systems.
• Implement DevSecOps best practices—including secrets management, environment hardening, and secure deployment patterns—to ensure compliance and operational resilience.
• Help define and enforce MLOps standards, documentation, and reusable patterns that improve efficiency and reduce technical debt across teams.
• Support troubleshooting and root-cause analysis of pipeline issues, infrastructure problems, or performance degradation in deployed ML models.
• Stay current with emerging MLOps tools, cloud-native ML technologies, distributed training methodologies, and best practices in ML lifecycle management.

Benefits

• The estimate displayed represents a typical annual salary range for this position.
• Annual salary is just one aspect of Steampunk’s total compensation package for employees.
• Learn more about additional Steampunk benefits here.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level