Posted:17 hours ago|
Platform:
Work from Office
Full Time
Job Description We are seeking a highly skilled ML/MLOps Engineer with an overall experience 5 years with 3 years as ML Engineer particularly in building and managing ML pipelines using MLFlow or CML (Cloudera Machine Learning). The ideal candidate has successfully built and deployed at least two MLOps projects using MLFlow or similar services, with a strong foundation in infrastructure as code and a keen understanding of MLOps best practices. Key Responsibilities Maintain and enhance existing ML pipelines in On Premise with a focus on infrastructure as code. Implement minimal but essential pipeline extensions to support ongoing data science workstreams. Convert the Data Science notebooks into production ready deployable components. Build ML pipelines for training, inference, monitoring. Document infrastructure usage, architecture, and design using tools like Confluence, GitHub Wikis, and system diagrams. Act as the internal infrastructure expert, collaborating with data scientists to guide and support ML model deployments. Research and implement optimization strategies for ML workflows and infrastructure. Work independently and collaboratively with cross-functional teams to support ML product Qualifications 6+ years of hands-on MLOps experience with Git Actions, Jenkins or any equivalent tools. Strong knowledge of ML workflow, MLOps concepts like model governance, model monitoring, d
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