Staff Machine Learning Operations Engineer
Description For Staff Machine Learning Operations Engineer
SciTec is seeking an experienced Staff Machine Learning Operations (MLOps) Engineer to join and shape their new MLOps team. This role is crucial for deploying and optimizing machine learning models in high-availability systems for both unclassified and classified environments. The position offers a unique opportunity to evangelize MLOps practices and contribute to developing an on-premises development platform.
The role involves working with cutting-edge technologies including Kubernetes, Docker, and Terraform, while implementing advanced deployment strategies and maintaining high-performing ML models. You'll be responsible for monitoring model performance, implementing automated retraining pipelines, and ensuring system reliability and uptime.
As a Staff MLOps Engineer, you'll collaborate with cross-functional teams, mentor junior members, and play a key role in building a collaborative and innovative team culture. The position requires strong expertise in Python, ML platforms, and infrastructure management tools, with preferred experience in C++/Rust and distributed systems.
SciTec offers an attractive compensation package including stock ownership, comprehensive benefits, and professional growth opportunities. The company's focus on defense, intelligence, and space solutions provides a meaningful context for your work. Located in Boulder, Colorado, you'll be part of a dynamic team pushing the boundaries of MLOps in mission-critical applications.
This role is perfect for someone who combines technical expertise with leadership abilities and wants to make a significant impact in a growing field. The position offers both technical challenges and the opportunity to shape the future of ML operations in classified environments.
Responsibilities For Staff 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
- Work with cross-functional teams to integrate and enhance ML systems
- Mentor junior team members and contribute to team culture
Requirements For Staff Machine Learning Operations Engineer
- 4+ years experience deploying/maintaining ML models in production
- Proficiency in Python for automation and scripting
- Experience with CI/CD pipelines
- Familiarity with distributed environments and frameworks
- Knowledge of MLflow, Kubeflow, or similar platforms
- Experience with Kubernetes and Terraform
- 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 Staff 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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