MLOps Engineer @ Devire

2 days ago

Remote, Czech Republic Devire Full time

2+ years of professional experience in ML Ops or ML engineering, particularly in productionizing and scaling ML models, Broad familiarity with Azure cloud environment and Databricks, including its setup and maintenance as an ML platform, Advanced proficiency with Python and SQL in version control systems (git) plus their use in building ML & data pipelines, Proven experience with software development best practices including testing, continuous integration, and DevOps tools, Good understanding of data science lifecycle and the way data scientists work to deliver value, Familiarity with agile software development lifecycle (SCRUM, Kanban, etc.), Attention to clarity of code, ease of development, and correctness of implementations Business-ready command of English, written and spoken. Devire IT Outsourcing is a form of collaboration dedicated to IT professionals, based on the principles of self-employment – ​​B2B – and implementing projects for clients pursuing innovative and cutting-edge projects. Our client is a global leader in the food industry, which has been providing innovative and high-quality products for over 150 years, shaping the daily choices of millions of consumers. We are seeking an MLOps Engineer for this client. B2B contract,Rate: 125-140 PLN/h net + VAT,Location: Remote collaboration (occasional office visits in Warsaw),Conversational English required. Benefits package (medical care, sports card, life insurance), Long-term cooperation, Flexible working hours, Polish time zone. ,[Optimize, standardize and implement data science and machine learning solutions at scale and in cloud-based environments (Azure),, Participate in the end-to-end lifecycle of data science projects through the use of DevOps, code, experiment and model management, CI/CD and further industry best practices,, Write well-designed, testable, efficient code,, Work closely with engineering to continuously improve the way we consume data and deploy models in production,, Design and lead on monitoring, troubleshooting, debugging and incident management for our ML pipelines,, Be a trusted advisor and evangelist to the team and stakeholders on various aspects of ML Ops, from scaling and throughput, to infrastructure and deployment strategies.] Requirements: Azure Cloud, Databricks, Python, SQL, Version control system, Data pipelines, Testing, Continuous integration, DevOps, Data science, Kanban

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