Machine Learning Operations Engineer (1463)
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Job Location:
Augusta, ME - USA
Monthly Salary:
Not Disclosed
Posted on:
Yesterday
Vacancies:
1 Vacancy
Job Summary
Referral Eligible
Build and Secure the ML Platform That Powers Mission Systems
We are looking for a hands-onMLOps Engineer who understands that deploying machine learning in production is not just about models its about reliable pipelines hardened infrastructure secure containers reproducible builds and audit-ready automation.
In this role you will design and operate the secure ML delivery platform that data scientists and developers depend on. Youll embed security directly into CI/CD infrastructure-as-code and container workflows so that ML systems can be deployed quickly safely and compliantly in a regulated government environment.
If you enjoy building pipelines automating guardrails hardening Kubernetes and making security invisible through great engineering this role is for you.
What the role will actually do:
- Build and maintain secure CI/CD pipelines for ML and application workloads
- Create repeatable hardened container and Kubernetes deployment patterns
- Automate vulnerability scanning SCA image scanning and policy gates
- Implement policy-as-code and security controls that run automatically in pipelines
- Improve Infrastructure-as-Code to reduce drift and standardize environments
- Enable centralized logging monitoring and alerting for security and operations visibility
- Work directly with developers and data scientists to shift security left without slowing delivery
- Support RMF/ATO readiness by generating evidence through automation (not paperwork)
- Harden systems using STIG-aligned configurations where required
- Participate in incident response root cause analysis and continuous improvement
- Create runbooks and operational documentation that engineers actually use
Job Qualifications:
- Experience with TensorFlow and/or PyTorch in production environments
- Hands-on experience with CI/CD pipelines container builds and deployment workflows
- Strong scripting/automation skills (Python Bash or similar)
- Experience with Kubernetes Docker/Podman and secure container practices
- Understanding of least privilege secrets handling patching logging and vulnerability management
- Experience operating in regulated or compliance-driven environments
- Ability to clearly communicate technical risk and document processes
Nice to Have/Preferred (but not required):
- Familiarity with NIST 800-53 RMF or ATO processes
- Experience implementing DISA STIG-aligned configurations
- Experience with tools like Ansible OpenSCAP Splunk/ELK/OpenSearch/Loki/Sentinel
- Experience with RHEL or RHEL-based systems
- Background in on-prem or hybrid segmented network environments
- Ops certifications (RHCSA or similar)
Why Engineers Like This Role
- Youre not bolting security on after the fact youre engineering it into the platform
- Real ownership of ML delivery pipelines not just maintenance
- Work that blends MLOps DevOps Security Engineering and Platform Engineering
- Opportunity to build automation that replaces manual compliance effort
- Mission-driven environment where your work directly supports operational capability
Education/Experience Requirements
- DoD 8570 IAT Level II (Security / SSCP or equivalent)
- Bachelors degree or equivalent experience
- 36 years in MLOps DevOps DevSecOps Platform Systems or Security Engineering
Details
- Full-time
- Less than 5% travel
What this job really is
You are the engineer who makes it possible to deploy ML systems securely repeatably and audit-ready without slowing developers down.
Clearance Type:
Requires a current TS/SCI. Employment is contingent on having the required active security clearance.
Zapata Technology is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race color religion sex national origin sexual orientation gender identity disability or protected veteran status.
Zapata Technology Inc. provides reasonable accommodation to applicants who are veterans or who have disabilities and are unable to fully use our company application system. If you need a reasonable accommodation for any part of the application and hiring process please notify Christina Hall EEO Coordinator at
Required Experience:
IC
