Senior Machine Learning Operations Engineer
Description For Senior Machine Learning Operations Engineer
SciTec is seeking an experienced Machine Learning Operations (MLOps) Engineer to join and shape their new MLOps team in Boulder, Colorado. This role focuses on deploying and optimizing machine learning models for always-on, high-availability systems in real-world, real-time unclassified and classified environments. The position offers a competitive salary range of $141,000-$168,000 and comprehensive benefits including ESOP, 401k, and full medical coverage.
The ideal candidate will have 8+ years of experience leading large-scale ML model deployments and scaling production environments. They will be responsible for implementing advanced deployment strategies, developing modular ML pipelines, and building scalable infrastructure using cutting-edge technologies like Kubernetes, Docker, and Terraform. The role requires expertise in Python, distributed systems, and workflow orchestration tools.
This is a unique opportunity to evangelize MLOps practices and contribute to the development of an on-premises development platform for mission-critical applications. The position offers significant growth potential, working with cross-functional teams and mentoring junior members while driving innovation in defense and space solutions.
The company provides an excellent benefits package including stock ownership, profit sharing, comprehensive insurance coverage, and flexible work arrangements. This role is perfect for a technical leader who wants to make a significant impact in the defense and space sector while working with cutting-edge ML technologies.
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
- Develop modular and flexible ML pipelines
- Build and manage scalable infrastructure using Kubernetes, Docker, Terraform
- Design and implement an on-premises development platform using Kubeflow
- Set up monitoring, logging, and alerting systems
- Optimize performance metrics while ensuring fault tolerance
- Work with cross-functional teams to integrate and enhance ML systems
- Define touchpoints with DevOps and Data Engineering
- 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 designing workflows using MLflow or Kubeflow
- Expertise in architecting complex Kubernetes and Terraform configurations
- Bachelor's, Master's, or PhD in Computer Science, Engineering, or related field
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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