Senior Machine Learning Operations Engineer
Description For Senior Machine Learning Operations Engineer
SciTec is seeking an experienced Machine Learning Operations (MLOps) Engineer to join their Defense, Intelligence, & Space Solutions division. This role presents a unique opportunity to shape and lead a new MLOps team, focusing on deploying and optimizing machine learning models for mission-critical, high-availability systems in both unclassified and classified environments. The position requires extensive expertise in Python, Kubernetes, and ML infrastructure, with responsibilities spanning from model deployment to platform development. The ideal candidate will have 8+ years of experience leading large-scale ML deployments, strong architectural skills, and the ability to mentor junior team members. The role offers competitive compensation ($141,000-$168,000) and comprehensive benefits, including ESOP, 401k, and full medical coverage. Located in Boulder, Colorado, this position provides an opportunity to work on cutting-edge ML systems while contributing to important defense and intelligence initiatives. The role combines technical leadership with hands-on engineering, requiring both deep technical expertise and strong collaborative skills.
Responsibilities For Senior Machine Learning Operations Engineer
- Deploy and maintain high-performing ML models in real-time environments
- Monitor deployed models for drift and implement automated retraining pipelines
- Implement advanced deployment strategies (Blue-Green, Canary, Champion-Challenger)
- Develop modular and flexible ML pipelines
- Build and manage scalable infrastructure using Kubernetes, Docker, Terraform
- Design and implement on-premises development platform using Kubeflow
- Set up monitoring, logging, and alerting systems
- Optimize performance metrics and ensure fault tolerance
- Work with cross-functional teams to integrate ML systems
- Mentor junior team members
Requirements For Senior Machine Learning Operations Engineer
- 8+ years experience leading large-scale ML model deployments
- Expertise in architecting Python applications for large-scale systems
- Proven leadership in designing enterprise-grade CI/CD systems
- Advanced expertise in designing distributed pipelines with Protobufs and ZeroMQ
- Advanced expertise in MLflow or Kubeflow workflows
- Expertise in Kubernetes and Terraform configurations
- Bachelor's, Master's, or PhD in Computer Science, Engineering, or related field
- Strong problem-solving and analytical skills
- Excellent communication and collaboration capabilities
Benefits For Senior Machine Learning Operations Engineer
- Employee Stock Ownership Plan (ESOP)
- 3% Fully Vested Company 401K Contribution
- 100% company paid HSA Medical insurance
- 80% company paid Dental insurance
- 100% company paid Vision insurance
- 100% company paid Life insurance
- 100% company paid Long-term Disability insurance
- Short-term Disability insurance
- Annual Profit-Sharing Plan
- Discretionary Performance Bonus
- Paid Parental Leave
- Generous Paid Time Off
- Flexible Work Hours
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