The Role
Design and implement end-to-end MLOps frameworks on Azure Databricks, architect secure scalable ML platforms, collaborate with cross-functional teams to move models from experimentation to production, and maintain up-to-date best practices in Databricks and Azure tooling.
Summary Generated by Built In
This is a remote position.
For our client, we are looking for a specialist to join the AI & Apps team as a Databricks ML Engineer.
We are a dynamic team focused on building scalable and secure machine learning solutions in cloud environments. Our projects involve designing and deploying end-to-end MLOps pipelines and automated CI/CD processes using Databricks and Azure services. We leverage cutting-edge technologies such as MLflow, Feature Store, and Terraform to deliver robust, production-ready ML solutions.
What will you do?
- Design and implement end-to-end MLOps frameworks on Azure Databricks for standardized model lifecycle management.
- Architect secure, scalable, and cost-efficient ML platform to support ML model development, deployment, and monitoring.
- Collaborate with data scientists, ML engineers, and data engineers to streamline workflows from experimentation to production.
- Keep up with the latest updates in Databricks, MLOps tooling, and Azure technologies.
Requirements
- Proficiency in Python (3+ years) for ML models development and automation.
- Deep expertise in the Databricks platform (Unity Catalog, Feature Store, MLflow, Declarative Automation Bundles).
- Solid understanding of MLOps practices e.g.: experiment tracking, model registry, deployment patterns and A/B testing.
- Experience with Spark/PySpark and distributed data processing on Databricks.
- Very good command of Polish (C1 level) and English (B2 level).
Nice to have:
- Exposure to LLMOps and operationalizing large language models (LLMs), including RAG architectures, vector databases, and Databricks Mosaic AI.
- Familiarity with Azure AI Services (Azure OpenAI, AI Search, Document Intelligence).
Soft skills:
- Analytical Thinking - ability to interpret data, identify trends, and provide actionable insights to drive business decisions.
- Problem-Solving Skills - proactively identify and resolve issues related to BI systems, ensuring smooth operations and data accuracy.
- Effective Communication - ability to explain technical concepts to non-technical stakeholders clearly and concisely, fostering understanding and collaboration.
- Attention to Detail - meticulous in data validation, report generation, and ensuring data quality across BI platforms.
- Team Collaboration - strong interpersonal skills to work effectively in cross-functional teams, coordinating with IT, business analysts, and other stakeholders.
- Adaptability and Continuous Learning - open to learning new tools and technologies in the rapidly evolving BI landscape and adjusting to changing business needs.
Benefits
- Flexible working hours.
- Private medical care (Medicover) or Multisport card - your choice.
- Modern, spacious office designed for collaboration and focus.
- Unlimited access to Microsoft/Snowflake technology.
- Work from anywhere - home, a coffee shop, or wherever you're most productive.
Skills Required
- Proficiency in Python (3+ years)
- Deep expertise in Databricks platform (Unity Catalog, Feature Store, MLflow, Declarative Automation Bundles)
- Solid understanding of MLOps practices (experiment tracking, model registry, deployment patterns, A/B testing)
- Experience with Spark/PySpark and distributed data processing on Databricks
- Very good command of Polish (C1) and English (B2)
- Exposure to LLMOps, operationalizing LLMs, RAG architectures, and vector databases (nice to have)
- Familiarity with Azure AI Services (Azure OpenAI, AI Search, Document Intelligence) (nice to have)
- Experience with Terraform (infrastructure as code) (nice to have)
- Soft skills: analytical thinking, problem solving, effective communication, attention to detail, team collaboration, adaptability
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The Company
What We Do
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