ML Ops Engineer

Join us and receive a $3000 sign-on bonus!

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

WHAT YOU WILL DO

• ML Infrastructure Support and Development: Build and maintain scalable ML infrastructure on Databricks, leveraging Unity Catalog and feature stores to support model development and deployment;
• Drift Detection Frameworks: Design and implement frameworks for detecting data and model drift, ensuring continuous monitoring and high reliability of ML models in production;
• Model Calibration & Versioning: Develop model calibration frameworks and establish versioning practices to maintain transparency and reproducibility across the ML lifecycle;
• Low-Latency Orchestration: Design and optimize reinforcement learning (RL) orchestration pipelines, including Contextual Bandits, for real-time execution in low-latency environments;
• Automated Training Pipelines: Create automated frameworks for training, retraining, and validating ML models, enabling efficient experimentation and deployment;
• CI/CD for ML: Implement CI/CD best practices to streamline the deployment and monitoring of ML models, integrating with Databricks workflows and Git-based version control systems;
• Collaboration: Work closely with ML Scientists to ship, deploy, and maintain models;
• Monitoring & Optimization: Build tools for model performance monitoring, operational analytics, and drift mitigation, ensuring reliable operation in production environments.

MUST HAVES

• 3+ years in MLOps, ML Engineering, Data Engineering or related roles, focusing on deploying and managing ML workflows in production environments;
• 5+ years of experience using Python;
• Proficient in using Databricks (2-3 years), Apache Spark, ML Flow, Unity Catalog, and feature stores;
• Familiarity with ML lifecycle tools such as MLflow, Kubeflow, and Airflow;
• Strong knowledge of Git workflows, CI/CD practices, and tools like GitLab or similar;
• Strong understanding of model performance monitoring, drift detection, and retraining workflows;
• Upper-Intermediate English level.

THE BENEFITS OF JOINING US

- Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.

- Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.

- A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.

- Flextime: Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office, whatever makes you the happiest and most productive.