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Experience in DevOps and/or MLOps establishing CI/CD for large machine learning models*Strong bonus experience: 1 - 2 years of deep learning/computer vision/natural language processing/machine learning/computer science with equivalent industry experience (or, in exceptional cases, BS with a proven track record of relevant industry or transferrable experiences.
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Bachelor’s or Master’s degree, or equivalent practical experience, in computer science, machine learning, software engineering, data engineering, DevOps, or related field. 5+ years of experience working in MLOps, machine learning engineering, software engineering, data engineering, DevOps, or related roles.
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Hands-on DevOps experience – CI/CD in Jenkins, Bitbucket, Kubernetes, and OpenShift. Good to have in-depth knowledge of machine learning frameworks or libraries such as TensorFlow, Keras, PyTorch, etc.
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Software Engineering & DevOps: Version Control: Familiarity with tools like Git. Continuous Integration/Continuous Deployment: Knowledge of pipelines and tools like Jenkins, Travis CI. Containerization: Familiarity with Docker, Kubernetes, etc., for scalable deployment of data science applications.
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Experience in supporting Deep Learning, Machine Learning or HPC networking infrastructures; experience with networking technologies as well as understanding deep learning frameworks such as TensorFlow or PyTorch.
$112,000 - $224,250 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with Entity Framework, Azure DevOps, Azure, and Data Visualisation tools are beneficial. Experience with ML & AI (Keras, TensorFlow, CAFFE, PyTorch) Experience with Entity Framework, Azure DevOps, Azure, and Data Visualisation tools are beneficial.
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Hands on DevOps experience – CI/CD in Jenkins , Bitbucket, Kubernetes ,OpenShift. Good to have in-depth knowledge in machine learning frameworks or libraries such as TensorFlow, Keras, PyTorch, etc.
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Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn). · Knowledge of DevOps principles and tools (e.g., CI/CD pipelines, Terraform.
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Experience and good understanding of Machine Learning / Python / Java / Google Cloud / DevOps / CICD. Experience using Machine Learning tools (pytorch, tensorflow, xgboost etc). Experience in Software Craftsmanship such as Paired Programming, Test Driven Development, DevOps etc.
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Preferred Skills:- Previous experience as a software engineer, applied mathematician, or in roles involving DevOps, MLOps, Databricks, and Apache Spark is highly regarded. Key Responsibilities:- Design, develop, and deploy advanced machine learning models and algorithms, leveraging deep learning frameworks such as PyTorch and TensorFlow.
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Apache Spark AWS AI Services AWS S3 AWS SageMaker Azure Cognitive Services Azure DevOps Azure Machine Learning Dataiku GCP Vertex AI Vertex AI. Experience with ML deep learning TensorFlow PythonNLP.
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Experience in distributed version control systems and DevOps tools, such as GitLab, Git, Docker, and Kubernetes. Skills You’ll Bring:Proficiency in ML and DL frameworks, such as scikit-learn, TensorFlow, and PyTorch.
$116,811.4 - $129,587.6 a yearFull-timeRemoteExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with a software lifecycle management tool such as Azure DevOps or JIRA.Experience with writing unit tests. Experience with one of the following machine learning frameworks: scikit-learn, pytorch, tensorflow.
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A multinational organization with 48 offices in 19 countries and the possibility to work abroad. Ability to understand tools used by data scientist and experience with software development and test automation.
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Demonstrated proficiency in applicable programming languages such as Python, Java, SQLExperience with ML and NLP libraries (e.g., TensorFlow, PyTorch, NLTK, spaCy, Scikit-learn. Strong understanding of data structures, algorithms, ML DevOps (build, continuous integration, deployment) and best practices using DevOps framework and GitHub. Familiarity with healthcare data standards and experience in working with EHRs, medical coding, or risk adjustment is highly desirable.
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