Senior MLOps Engineer

3 weeks ago

Chicago, United States Masentó Group Full time

Senior MLOps Engineer - Michigan


Our client is a leading industrial manufacturing company based in Chicago, committed to driving innovation and efficiency within the manufacturing sector. Known for producing high-quality industrial products and solutions, they are at the forefront of integrating cutting-edge technologies to optimize their operations and product offerings. With a strong focus on digital transformation, they are now looking to expand their team with a talented MLOps Engineer to support their machine learning (ML) initiatives.


Role Responsibilities:

  • Design, build, and maintain scalable and efficient ML infrastructure for deploying and monitoring models in production.
  • Work closely with data science teams to automate model training, evaluation, and deployment pipelines.
  • Develop and implement CI/CD practices for ML models, ensuring they are versioned, reproducible, and compliant with organizational standards.
  • Monitor, troubleshoot, and resolve issues related to ML models in production, ensuring minimal downtime.
  • Integrate and operationalize Generative AI (GenAI) models, ensuring they meet performance and security standards for production use.
  • Manage data pipelines to ensure consistent and reliable data flow for model training and prediction.


Key Skills:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
  • Proven experience in MLOps, DevOps, or related roles with a focus on machine learning infrastructure.
  • Proficiency in cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization tools like Docker and Kubernetes.
  • Proficiency in programming languages like Python, with a focus on ML deployment and automation & scripting language i.e Bash
  • Knowledge of ML life cycle management frameworks (e.g. MLFlow) and ML platforms (e.g. Azure Machine Learning, Databricks Model Hosting).
  • Familiarity with generative AI, Large Language Models (LLMs) and other Foundation Model applications.
  • Experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).

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