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.
You will contribute to the growth of our AI & Data Exploitation Practice!
Qualifications
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.
Preferred certifications
AWS ML Specialty
AWS DevOps Engineer
Azure Data Scientist Associate
Google Professional Machine Learning Engineer
Databricks Machine Learning Associate/Professional
About steampunk
Steampunk relies on several factors to determine salary, including but not limited to geographic location, contractual requirements, education, knowledge, skills, competencies, and experience. The projected compensation range for this position is $115,000 to $150,000. 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.
Identity Statement
As part of the application process, you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.
Steampunk is a Change Agent in the Federal contracting industry, bringing new thinking to clients in the Homeland, Federal Civilian, Health and DoD sectors. Through our Human-Centered delivery methodology, we are fundamentally changing the expectations our Federal clients have for true shared accountability in solving their toughest mission challenges. If you want to learn more about our story, visit http://www.steampunk.com.
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law. Steampunk participates in the E-Verify program.
