Ml Ops Engineer Id38029 – $3,000 Sign-On Bonus

buscojobs Argentina; Córdoba; Híbrido; EUR 30.000 - 50.000; Jornada completa

Descripción de la vacante

A technology company is seeking an experienced professional for a role in MLOps and ML Engineering. You will build scalable ML infrastructure and design frameworks for model monitoring. Candidates should have 3+ years in related roles and proficiency in Python and Databricks. The position offers a competitive USD-based salary and flexible work options for a balanced lifestyle.

Servicios

Professional growth opportunities

Competitive USD-based compensation

Flexible schedule options

Formación

• 3+ years in MLOps, ML Engineering, or related roles focusing on ML workflows.
• 5+ years of experience with Python.
• Proficiency with Databricks, Apache Spark, MLflow, and feature stores.

Responsabilidades

• Build and maintain scalable ML infrastructure.
• Design frameworks for detecting data drift.
• Develop model calibration frameworks.

Conocimientos

MLOps

ML Engineering

Data Engineering

Python

Databricks

Apache Spark

MLflow

CI/CD practices

Git workflows

Upper-Intermediate English

Herramientas

Databricks

Kubeflow

Airflow

Descripción del empleo

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 that has earned us 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

• Build and maintain scalable ML infrastructure on Databricks, using Unity Catalog and feature stores for model development and deployment;
• Design frameworks for detecting data and model drift to ensure continuous monitoring of ML models in production;
• Develop model calibration frameworks and establish versioning practices for transparency and reproducibility;
• Design and optimize reinforcement learning orchestration pipelines, including Contextual Bandits, for real-time low-latency environments;
• Create automated training, retraining, and validation frameworks for ML models;
• Implement CI / CD practices to streamline ML deployment and monitoring, integrating with Databricks and Git workflows;
• Collaborate with ML Scientists to deploy, maintain, and improve models;
• Build tools for model performance monitoring, operational analytics, and drift mitigation.

MUST HAVES

• 3+ years in MLOps, ML Engineering, Data Engineering, or related roles focusing on ML workflows in production;
• 5+ years of experience with Python;
• Proficiency with Databricks (2-3 years), Apache Spark, MLflow, 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;
• Understanding of model performance monitoring, drift detection, and retraining workflows;
• Upper-Intermediate English level.

THE BENEFITS OF JOINING US

• Professional growth through mentorship, TechTalks, and personalized development plans;
• Competitive USD-based compensation and budgets for education, fitness, and team activities;
• Opportunity to work on exciting projects with top-tier clients, including Fortune 500 companies;
• Flexible schedule options, including remote work and office presence, for work-life balance.

Your application process continues via email. Please complete your registration on our Applicant Site to proceed; incomplete registration will result in termination of your application.