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 makes you a great fit?
Key technologies
Python | ML | Databricks | Spark/PySpark
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Proficiency in Python (3+ years) for ML models development and automation.
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Deep expertise in the Databricks platform (Unity Catalog, Feature Store, MLflow, Declarative Automation Bundles)
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Solid understanding of MLOps practices e.g.: experiment tracking, model registry, deployment patterns and A/B testing.
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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.
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.
Our benefits
Your journey with us starts here:
1. Initial Screening: If you meet our requirements, our recruiter will reach out to you for a chat about your motivations and expectations. Get ready to share your passion!
2. Technical Interview: Next, you'll be invited to showcase your skills in an interview with one of our technical experts or team members. This is your chance to shine and demonstrate your expertise.
3. Final Interview: Finally, you'll have the opportunity to meet your future Team Lead. This is the perfect moment to learn more about the role, the team, and to ask any questions you might have.