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Remote Machine Learning Ops Engineer jobs

Browse top remote and work from home Machine Learning Ops Engineer jobs at remote companies. Apply now to fully remote opportunities.

What does a Machine Learning Ops Engineer do?

The Machine Learning Ops (MLOps) Engineer is a key role in the software development industry that focuses on managing and optimizing the deployment of machine learning models into production. This role, which may also be referred to as a Machine Learning Engineer or Data Ops Engineer, involves responsibilities such as collaborating with data scientists to understand model requirements, automating the deployment process, monitoring model performance, and ensuring that models are updated and maintained over time. Required skills include a strong understanding of machine learning concepts, programming languages like Python or R, and familiarity with cloud platforms such as AWS or Azure. Typical tools used in this role include TensorFlow, Docker, and Kubernetes. By effectively bridging the gap between development and operations, MLOps Engineers help ensure that machine learning models are reliable, scalable, and integrated smoothly into software applications, ultimately enhancing the overall software development life cycle.

46 jobs found

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Intermediate Backend Engineer, ModelOps:MLOps at GitLab
Americas - Remote EMEA - Remote $ 98,000 - 210,000 USD / year Machine Learning Ops Engineer Full-time Mid-level Agile CI/CD Deep learning Docker Equity compensation GitLab Go HTML Kubernetes LESS Large Language Models Machine Learning Open source Paid time off Parental leave PyTorch Python Ruby Ruby on Rails Scikit Swift TensorFlow
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