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 in Boulder, Colorado. This role presents a unique opportunity to work on mission-critical applications in both unclassified and classified environments within the defense and space sector.
The position focuses on deploying and optimizing machine learning models for always-on, high-availability systems in real-world, real-time environments. As a key member of a new and growing team, you'll have the chance to evangelize MLOps practices and contribute to the development of an on-premises development platform.
The role requires expertise in deploying and maintaining high-performing ML models, implementing advanced deployment strategies, and building scalable infrastructure using modern tools like Kubernetes, Docker, and Terraform. You'll be responsible for setting up robust monitoring systems, optimizing performance metrics, and working closely with cross-functional teams.
SciTec offers a comprehensive benefits package including ESOP, 401k with company contribution, full medical coverage, and various insurance benefits. The salary range of $96,000-$115,000 reflects the senior nature of the position and the company's commitment to competitive compensation.
The ideal candidate will have 4+ years of experience in ML model deployment, strong Python programming skills, and a deep understanding of MLOps practices. This role offers the opportunity to work on cutting-edge technology while contributing to important defense and space initiatives, making it perfect for someone who wants to make a significant impact in a growing field.
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
- 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
- Mentor junior team members
Requirements For Staff Machine Learning Operations Engineer
- 4+ years experience including deploying/maintaining ML models in production
- Proficiency in Python coding
- 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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