At Cloudfide, we engineer solutions where data truly becomes an accelerator for innovation. We build and evolve large-scale Big Data and cloud-native platforms for global clients, including leaders in retail and the Fortune 500. We process massive, complex datasets, operate fully in the cloud ecosystem, and work with the latest technologies, including AI, ML, MLOps, and modern data architectures.
Our projects have measurable, real‑world impact - from enhancing customer experiences at scale to empowering data-driven decision-making in high‑visibility global organizations. As we continue to grow, youll have the opportunity to shape solutions, mentor others, drive architecture decisions, and take ownership of strategic initiatives.
Opportunity Overview
As a Mid Data Scientist, you will design and deliver production-grade machine learning solutions in a cloud-native environment, working with cutting-edge technologies including Azure, Databricks, and Large Language Models. Youll tackle complex, real-world data problems for international clients - with a particular focus on computer vision and image recognition use cases.
Expect hands-on work with neural networks, LLMs, and modern MLOps practices across high-visibility projects for Fortune 500 organizations.
Youll join a team of passionate engineers and data scientists who value technical excellence, collaboration, and continuous growth.
responsibilities :
Designing, developing, and deploying production-grade machine learning and deep learning models using Python, Azure ML, and Databricks.
Building and optimizing computer vision and image recognition solutions using OpenCV and related frameworks.
Working with LLMs, structured outputs, and LangChain to develop intelligent, data-driven applications.
Managing end-to-end ML workflows - from data preparation and model training to evaluation, deployment, and monitoring.
Collaborating with data engineers, architects, and business stakeholders to translate complex requirements into scalable ML solutions.
Managing code, experiments, and model versioning using Git and Databricks Asset Bundles.
Contributing to MLOps practices - ensuring models are reproducible, maintainable, and production-ready.
Staying up to date with emerging research and technologies in AI, ML, and computer vision.
requirements-expected :
3+ years of commercial experience as a Data Scientist.
Strong proficiency in Python and hands-on experience with machine learning and deep learning frameworks.
Solid understanding of neural network architectures and model training best practices.
Practical experience with computer vision techniques - image classification, object detection, or image recognition.
Familiarity with Azure ML, Databricks, or similar cloud-based ML platforms.
Experience with LLMs, LangChain, or structured output techniques.
Hands-on knowledge of OpenCV and image processing pipelines.
Comfortable with Git and collaborative development workflows.
Strong problem-solving skills with the ability to work independently on technically challenging tasks.
Fluent English communication, able to collaborate effectively across international teams.
offered :
Benefits:
MyBenefit platform / Multisport
Enel‑Med private medical care
Professional Growth:
Annual 2,000 PLN development budget
Access to e‑learning platforms
Real opportunities to expand responsibility and lead initiatives - most of our Leads come from internal promotions
As the company continuously grows, you get real opportunities to expand your responsibilities, explore new areas, and even take ownership of your own initiatives.
Work Environment:
Long-term cooperation: UZ or B2B (we value stable, lasting relationships)
Remote-first, work from anywhere in the world (workation)
Flexible hours & strong focus on work-life balance
Collaboration with top engineers you can truly learn from
Flat structure - every voice counts, and you help shape the company
Culture & Integration:
Company-wide trips (including international ones)
Team integration budgets
Open communication and supportive, passionate teams
benefits :
private medical care
sharing the costs of professional training & courses
