ML Infrastructure Specialist

1 semana atrás

Blumenau, Santa Catarina, Brasil beBeeMachineLearning Tempo inteiro US$100.000 - US$150.000
About the Role

We are seeking a highly skilled ML Ops Engineer to join our team. As an ML Ops Engineer, you will be responsible for building and maintaining scalable ML infrastructure on Databricks, leveraging Unity Catalog and feature stores to support model development and deployment.

Key Responsibilities:
  • Data Engineering:
    • Design and implement frameworks for detecting data drift and model drift, ensuring continuous monitoring and high reliability of ML models in production;
    • Develop model calibration frameworks and establish versioning practices to maintain transparency and reproducibility across the ML lifecycle;
  • Model Deployment:
    • Optimize reinforcement learning (RL) orchestration pipelines, including Contextual Bandits, for real-time execution in low-latency environments;
    • Create automated frameworks for training, retraining, and validating ML models, enabling efficient experimentation and deployment;
  • Collaboration and Communication:
    • Implement CI/CD best practices to streamline the deployment and monitoring of ML models, integrating with Databricks workflows and Git-based version control systems;
    • Collaborate with ML Scientists to ship, deploy, and maintain models;
    • Build tools for model performance monitoring, operational analytics, and drift mitigation, ensuring reliable operation in production environments.
Requirements:
  • At least 3 years of experience 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, 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;
  • Upper-Intermediate English level.
Benefits:

This role offers a unique opportunity to work with a talented team of engineers and scientists, contributing to the development of cutting-edge AI solutions.

Candidates Must-Haves:
  • Prior experience in building and deploying ML models;
  • Strong understanding of machine learning concepts and algorithms;
  • Excellent problem-solving skills and attention to detail.
About AgileEngine

We are an award-winning software company that creates innovative solutions for Fortune 500 brands and trailblazing startups.

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