The company is looking to deploy and optimize machine learning models for always-on, high-availability systems in real-world, real-time unclassified and classified environments.
Requirements
- Proficiency in writing clean, maintainable code for automation and basic scripting tasks
- Basic familiarity with MLflow, Kubeflow, or similar platforms for managing ML experiments and pipelines
- Familiarity with C++ and/or Rust
- Experience with workflow orchestration tools such as Airflow or Prefect
- Experience with distributed data processing frameworks such as PySpark
- Familiarity with SQL and modern database technologies (e.g., MinIO, Yugabyte)
- Experience with DVC, Ansible, Kustomize, Helm, Prometheus, and Grafana
Responsibilities
- Deploy and maintain high-performing ML models in real-time environments
- Monitor deployed models for drift or performance degradation and implement automated retraining pipelines
- Develop modular and flexible ML pipelines that ensure uptime and reliability
- Set up robust monitoring, logging, and alerting systems using Prometheus, Grafana, and Loki or similar systems
- Optimize performance metrics like inference latency and system throughput while ensuring fault tolerance
- Work with cross-functional teams to integrate and enhance ML systems
- Define touchpoints and handoffs with DevOps and Data Engineering to ensure seamless integration of ML workflows with existing infrastructure and data pipelines
Other
- Secret clearance
- 4+ years of experience, including deploying and/or maintaining at least one ML model or pipeline in a production environment
- Excellent communication and collaboration capabilities
- Ability to thrive in a dynamic, fast-paced environment
- Good written and verbal communication skills
- Detail oriented
- Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related technical field
- Relevant certifications (e.g., Certified Kubernetes Administrator, Certified Kubernetes Application Developer, Terraform Associate)
- Position location is on-site in Boulder, CO 5 days per week
