Databricks ML Engineer

This is a remote position. For our client, we are looking for a specialist to join the AI & Apps team as a Databricks ML [link removed] 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 [link removed] 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. 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. Originally posted on Himalayas