The Position We are looking for a DevOps Specialist with experience with MLOps to bridge the gap between machine learning development and production engineering. In this role, you will design, build, and maintain the infrastructure and tooling that enables our AI and ML Analysts and Engineers to rapidly develop, deploy, monitor, and iterate on machine learning models at scale.
The DevOps Specialist is a core member of the Geointelligence DevSecOps and MLOps team. You will work at the intersection of Software Engineering, DevOps, and Machine Learning - ensuring our AI and ML systems are reliable, reproducible, and efficient. This is a high-impact role that will shape how we deliver AI - powered products to our customers.
Responsibilities:
Platform
- Design and evolve a scalable, secure MLOps platform that include model registry, CI / CD / CT, feature store, experiment tracking, and monitoring built on Kubernetes, Terraform for both on premise and cloud (AWS)
- Develop reusable infrastructure-as-code modules for data ingestion, model serving, and auto scaling.
Model Lifecycle Management
- Implement automated CI / CD pipelines that take model code, data schemas, and container images from development to production with minimal down time
- Integrate model versioning with data lineage and meta data tracking
Operational Excellence
- Build observability platform for latency, throughput, drift detection, and resource utilization of live models
- Develop automated alerts and self healing mechanisms for model anomalies or hardware failures
Collaboration and Enablement
- Partner with AI / ML Analysts to translate research notebooks into production ready pipelines, providing tooling, best practice guidance, and code reviews
- Collaborate with Corporate IT, Technical Governance, and Platform Products to up-skill teams on MLOps best practices and platform usage.
Security and Compliance
- Implement data encryption in transit and at rest, role-based access control, and secure secret management meeting both government and industry standards.
- Participate in risk assessments and support audit activities for Geointelligence AI and ML systems.
Continuous Improvement
- Evaluate emerging technologies and recommend adoption where they add measurable value
- Contribute to open source components and publish internal libraries to foster a reusable ecosystem
Qualifications/ Requirements:
- Sc in Computer Science, B.Eng Engineering, Data Science, or related field
- 3+ years of software development experience with at least 2 years focused on MLOps
- Proficiency in Python and at least one compiled language such as C / C++, Go, Rust
- Proficiency with Docker containers and Kubernetes
- Infrastructure as code (Terraform, Ansible)
- CI / CD / CT tooling
- Model serving frameworks
- Experiment / metadata tracking
- Monitoring and Observability
- Cloud Platform
- Experience with AWS services for compute including EKS, storage, and AI / ML e.g. SageMaker / Bedrock
- Excellent communication - the ability to translate technical concepts for non-technical stakeholders
- Proactive problem solver, comfortable working in a fast paced, mission critical environment
Comments/Special Considerations:Successful candidates must obtain and hold
security clearance at the reliability status level, and pass security assessment for the
Controlled Goods Program (CGP).
The compensation range for this position is $78,000 - $108,000 annually. The specific compensation offered will be based on the qualifications and experience of the successful candidate.
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