Senior ML Platform Engineer

We are a team of tech enthusiasts on a mission to bring together the best minds in IT services and analytics. Our goal? To create cutting-edge IT and Analytical Hubs that empower our partners to become truly data-driven organizations.

We are looking for a hands-on Senior ML Platform Engineer to support one of hubQuest’s partners in building a global analytics solution. This is a unique opportunity to work on a high-impact internal platform used by Data Scientists across the organization to seamlessly build, run, and productionize machine learning pipelines.

This role is strongly MLOps-oriented, combining deep software engineering expertise with a strong understanding of ML lifecycle management, automation, and platform design.

What you'll be working on

You’ll contribute to the development of an internal ML enablement platform — a CLI + backend-based solution designed to make it easier and faster for Data Scientists to create, run, and productionize complex machine learning pipelines. These pipelines support strategic business decisions, including simulations and Bayesian optimizations that require regular manual tuning and input from business experts.

Your responsibilities will include:

• Building and evolving the MLOps framework for running, monitoring, and deploying DS pipelines.
• Designing and maintaining platform components to automate and simplify ML workflows.
• Developing CLI tooling to streamline local development and testing.
• Automating workflows using Databricks Workflows.
• Building and maintaining a FastAPI backend to expose results and trigger simulations/optimizations.
• Contributing to CI/CD processes using Azure DevOps.
• Working with Azure services like Web Apps, Redis, ADLS, and more.
• Collaborating closely with Data Scientists to improve the developer experience.

What we’re looking for

Must-have:

• 2+ years of experience as an MLOps Engineer in production environments.
• Strong software engineering skills in Python, especially in data-heavy contexts.
• 2+ years of data engineering experience.
• Experience with Azure DevOps, including CI/CD pipelines.
• Solid understanding of the ML lifecycle and infrastructure for ML workflows.
• Ability to design clean, modular, developer-friendly APIs and internal tools.
• Fluent in English.

Nice to have:

• Experience with FastAPI or similar Python frameworks.
• Familiarity with MLflow, Databricks, or Azure ML pipelines.
• Experience with PySpark for large-scale data processing.
• Experience building internal platforms or tooling for ML/DS teams.
• Understanding of orchestration patterns and scalable ML infra.

About the project

You’ll join a global, cross-functional Analytics team made up of Data Scientists, ML Engineers, MLOps Engineers, Software Developers, and more. The team spans several countries and is focused on creating scalable, smart data products to drive business decisions.

The platform you’ll help develop is a foundational layer for the organization's analytics capability — supporting local development, scaling on the cloud, triggering simulations and optimizations, and orchestrating deployments in a robust and automated way.

Why join us?

• Work at the intersection of ML platforms and MLOps.
• High-impact role focused on enabling ML at scale.
• Flexible remote or hybrid setup with a modern office in Warsaw.
• Join a diverse and experienced international team.
• No red tape – just real tech challenges and ownership.
• Benefits: private medical care, Multisport, access to online learning and certifications.
• Supportive, collaborative, and relaxed atmosphere.

Ready to build the future of ML platforms?

If you're passionate about empowering ML teams through engineering, automating workflows, and building tools that scale — apply now and join our mission at hubQuest!

Please add to your CV the following clause:

"I hereby agree to the processing of my personal data included in my job offer by hubQuest spółka z ograniczoną odpowiedzialnością located in Warsaw for the purpose of the current recruitment process.”

If you want to be considered in the future recruitment processes please add the following statement:

"I also agree to the processing of my personal data for the purpose of future recruitment processes.”