Senior ML Platform Engineer @ hubQuest

remote, poland, Poland

Type: n/a

Category: Engineering & Manufacturing

Requirements: English
Company: hubQuest
Region: remote, poland ,

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 ahands-on Senior ML Platform Engineerto support one ofhubQuests partnersin 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 stronglyMLOps-oriented, combining deep software engineering expertise with a strong understanding of ML lifecycle management, automation, and platform design.

What you''ll be working on

Youll contribute to the development of aninternal 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.

About the project

Youll join aglobal, cross-functional Analytics teammade 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 youll 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 ofML platformsandMLOps.
• High-impact role focused on enabling ML at scale.
• Flexible remote or hybrid setup with a modern office inWarsaw.
• 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!

Must-have:

• 2+ years of experience as anMLOps Engineerin production environments.
• Strong software engineering skills inPython, especially in data-heavy contexts.
• 2+ years ofdata engineeringexperience.
• Experience withAzure DevOps, including CI/CD pipelines.
• Solid understanding of theML lifecycleand infrastructure for ML workflows.
• Ability to design clean, modular, developer-friendly APIs and internal tools.
• Fluent in English.

Nice to have:

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

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 ahands-on Senior ML Platform Engineerto support one ofhubQuests partnersin 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 stronglyMLOps-oriented, combining deep software engineering expertise with a strong understanding of ML lifecycle management, automation, and platform design.

What you''ll be working on

Youll contribute to the development of aninternal 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 pipel

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