We are looking for a passionate Machine Learning Engineer to join our team and help build scalable, production‑ready ML solutions. You will work on cutting‑edge projects involving predictive modeling, MLOps, and cloud‑based deployments, leveraging platforms like Azure Databricks. This is an opportunity to shape the future of AI‑driven solutions in a dynamic and collaborative environment.

What makes you a great fit?

Key technologies

Python | Databricks | MLOps | MLflow | Azure Services

• Proficiency in Python 3+ years for data science and machine learning development.
• Hands‑on experience with Azure services and Databricks platform.
• Strong knowledge of machine learning algorithms and modeling techniques.
• Familiarity with MLOps practices, including MLflow for experiment tracking and model management.

Nice To Have

• Experience with Spark/PySpark and understanding of distributed data processing.
• Exposure to large language models (LLMs) and their practical applications.
• Knowledge of Docker and Kubernetes for containerization and orchestration.

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, develop, and deploy machine learning models for regression, classification, clustering, and time series forecasting.
• Manage and utilize Azure Databricks Feature Store, MLflow and Asset Bundles for efficient model lifecycle management.
• Collaborate with data scientists and engineers to optimize model performance and scalability.
• Ensure robust deployment strategies for ML models on Azure cloud environments.
• Stay abreast of the latest advancements in Databricks and Azure technologies.
• Exceptional problem‑solving and critical thinking abilities.

Your Journey With Us Starts Here

• 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!
• Technical Interview: Next, youll 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.
• Final Interview: Finally, youll 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.