Senior Azure MLOps Engineer @ hubQuest

2 tygodni temu

Warsaw, Polska hubQuest Pełny etat

You are invited to join our partner's Global Analytics unit which is a global, centralized team with the ambition to strengthen data-driven decision-making and the development of smart data products for day-to-day operations.
Currently we are looking for a Senior Azure MLOps Engineer as we are supporting our partner in developing Global Analytics unit which is a global, centralized team with the ambition to strengthen data-driven decision-making and the development of smart data products for day-to-day operations.
Team's essence is an innovative spirit, which permeates throughout the company, nurturing a data-first approach in every facet of the business. From sales and logistics to marketing and purchasing, our smart data products have been pivotal in rapid growth and operational excellence. As team expands its analytics solutions on a global scale, we are on the lookout for an experienced Senior Azure MLOps Engineer.
The Global Analytics team is a diverse collective of Data Scientists, Data Engineers, Business Intelligence Specialists, and Analytics Translators, with footprints across three continents and five countries. Its ethos revolves around fostering collaboration, driving innovation, and ensuring reliability. Together, we're committed to transforming whole organization into a leader in data-driven decision-making, leveraging global diversity to tackle challenges and create value.
The team has a lot of freedom to shape this, especially in the use of tools and technology, but also by introducing new concepts, solutions and ways of working.

advanced degree in Computer Science, Statistics, or a related STEM field
minimum of 5 years of experience in ML engineering or engineering support for data science in an industrial or commercial setting
proven experience with Azure cloud services and infrastructure
strong background in operationalizing Data Science projects using Azure
experience in deploying and managing ML models in production environments
advanced proficiency in Python, with nice-to-have experience in Django and FastAPI
expertise in DevOps tools and methodologies, such as Docker, Kubernetes, and CI/CD pipelines
experience with Azure DevOps, including CI/CD pipelines and releases, with test plans as a nice-to-have
proficiency in Git, with a focus on Trunk-based development; other Git branching strategies are a nice-to-have
solid understanding of RDBMS, with PostgreSQL as a nice-to-have
experience with Infrastructure as Code (IaC), specifically Bicep
strong skills in Bash scripting
familiarity with Azure Machine Learning, with Python SDK v2 as a nice-to-have
experience with Azure App Service, Azure Container Apps, Azure Data Lake Storage, and Azure Functions
strong software engineering skills, including unit testing and object-oriented programming (OOP)
ability to develop and enhance CI/CD pipelines for continuous integration and deployment during both development and production phases
solid understanding of machine learning algorithms and AI concepts, with hands-on experience in ML model development
experience in building and optimizing data pipelines, architectures, and datasets
ability to write high-quality, well-documented, and thoroughly tested code
experience in production deployment and the ability to design and deliver products with a modular approach
experience working in start-up environments or organizations with an agile culture, particularly in cross-functional teams
professional attitude and a strong service orientation
team player with the ability to work autonomously on complex projects
fluency in English, as it will be the primary language of communication
Nice to have:
experience with Pandas for data manipulation
familiarity with Spark and Databricks for big data processing
experience with DBT (Data Build Tool) for data transformations
You are invited to join our partner's Global Analytics unit which is a global, centralized team with the ambition to strengthen data-driven decision-making and the development of smart data products for day-to-day operations.
Currently we are looking for a Senior Azure MLOps Engineer as we are supporting our partner in developing Global Analytics unit which is a global, centralized team with the ambition to strengthen data-driven decision-making and the development of smart data products for day-to-day operations.
Team's essence is an innovative spirit, which permeates throughout the company, nurturing a data-first approach in every facet of the business. From sales and logistics to marketing and purchasing, our smart data products have been pivotal in rapid growth and operational excellence. As team expands its analytics solutions on a global scale, we are on the lookout for an experienced Senior Azure MLOps Engineer.
The Global Analytics team is a diverse collective of Data Scientists, Data Engineers, Business Intelligence Specialists, and Analytics Translators, with footprints across three continents and five countries. Its ethos revolves around fostering collaboration, driving innovation, and ensuring reliability. Together, we're committed to transforming whole organization into a leader in data-driven decision-making, leveraging global diversity to tackle challenges and create value.
The team has a lot of freedom to shape this, especially in the use of tools and technology, but also by introducing new concepts, solutions and ways of working.
,[collaborate with Data Scientists to understand business challenges and design smart data products, develop and enhance MLOps frameworks for Data Science projects, ensuring adherence to best practices, design and implement Azure-based cloud infrastructure to support the development and deployment of AI-driven applications, build and optimize Azure cloud-hosted, automated pipelines for running, monitoring, and retraining data science models in business applications, support Data Engineers in automating data ingestion and processing workflows, create and maintain workflows for training, testing, and deploying data science models into production environments in close collaboration with Data Scientists and Data Engineers, manage the life cycle of deployed ML applications, including new releases, change management, monitoring, and troubleshooting, implement frameworks for measuring and optimizing the quality of deployed solutions] Requirements: Azure, Python, Azure DevOps, Kubernetes, Docker, RDBMS, IaC, MLOps, Azure ML, Azure App Service, Azure Data Lake Storage, Azure Functions, Bash, Spark, Databricks, pandas, Django, FastAPI, PostgreSQL, Bicep, dbt Tools: Agile, Scrum. Additionally: Sport subscription, Private healthcare, Training budget, Small teams, International projects, Free coffee, Bike parking, Free beverages, In-house trainings, In-house hack days, Modern office, No dress code.

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