
Responsibilities:
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Define and implement the technical MLOps strategy and roadmap for the position
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Serve as a technical leader and mentor for MLOps engineers
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Design, build, and maintain scalable and reliable machine learning & CI/CD pipelines
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Ensure the efficient deployment, monitoring & Governance of AI models in production
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Collaborate with data scientists and engineers to optimize model performance and deployment
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Establish and enforce best practices for MLOps, including version control, model governance, and monitoring
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Evaluate and implement new MLOps tools and technologies
Required Skills:
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+8 years of relevant experience in Data Science or a related field 2 years of them in the MLOps field
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Extensive experience in designing and implementing MLOps strategies and pipelines
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Deep expertise in on-prem platforms and containerization technologies (e.g., Docker, Kubernetes)
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Strong proficiency in programming languages like Python and scripting languages
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Experience with CI/CD & MLOps tools as well as different ML frameworks
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Strong understanding of data engineering and software development principles
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Excellent communication and technical documentation skills
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Ability to work effectively in a complex and dynamic environment
Desirable Skills:
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Experience with feature stores and model registries
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Knowledge of data governance and compliance requirements
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Experience with different data platforms (Cloudera, Teradata, etc..)
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