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Ml ops engineer id38029 – $3,000 sign-on bonus

San Luis Potosí, S.L.P.
AgileEngine
De EUR 200,000 a EUR 400,000 al año
Publicada el 29 julio
Descripción

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 startups across 17+ industries. We are leaders in application development and ai/ml, with a people-first culture recognized by multiple best place to work awards.

if you're looking for growth, impact, and a caring team, we'd love to meet you!


what you will do

1. ml infrastructure support and development: build and maintain scalable ml infrastructure on databricks, leveraging unity catalog and feature stores for model development and deployment.
2. drift detection frameworks: design and implement frameworks for detecting data and model drift, ensuring continuous monitoring and high reliability of ml models in production.
3. model calibration & versioning: develop calibration frameworks and establish versioning practices for transparency and reproducibility in the ml lifecycle.
4. low-latency orchestration: design and optimize reinforcement learning (rl) orchestration pipelines, including contextual bandits, for real-time, low-latency environments.
5. automated training pipelines: create frameworks for training, retraining, and validating ml models to enable efficient experimentation and deployment.
6. ci/cd for ml: implement best practices for ci/cd to streamline ml deployment and monitoring, integrating with databricks and git workflows.
7. collaboration: work closely with ml scientists to ship, deploy, and maintain models.
8. monitoring & optimization: build tools for performance monitoring, operational analytics, and drift mitigation to ensure reliable production operation.


must haves

1. 3+ years in mlops, ml engineering, data engineering, or related roles focused on ml workflows in production.
2. 5+ years of experience using python.
3. proficiency with databricks (2-3 years), apache spark, mlflow, unity catalog, and feature stores.
4. familiarity with ml lifecycle tools such as mlflow, kubeflow, and airflow.
5. strong knowledge of git workflows, ci/cd practices, and tools like gitlab.
6. understanding of model performance monitoring, drift detection, and retraining workflows.
7. upper-intermediate english level.


the benefits of joining us

1. professional growth: mentorship, techtalks, and personalized growth plans.
2. competitive compensation: usd-based salary, education, fitness, and team activity budgets.
3. exciting projects: work with modern solutions for fortune 500 clients and leading brands.
4. flextime: flexible schedule with options for remote and in-office work.

your application doesn't end here! Check your email and complete your registration on our applicant site to proceed. Incomplete registration will result in termination of your application.

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