ML Ops Engineer ID38029 – 3,000 Sign-On Bonus

Join to apply for the ML Ops Engineer ID38029 – $3,000 Sign-On Bonus role at AgileEngine

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Join to apply for the ML Ops Engineer ID38029 – $3,000 Sign-On Bonus role at AgileEngine

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Join us and receive a $2,500 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.

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Seniority level

• Seniority level Mid-Senior level

Employment type

• Employment type Full-time

Job function

• Industries IT Services and IT Consulting

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