Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Building and operationalizing ML solutions across the Data & AI landscape with an accent on computer vision, forecasting, and LLM-enabled workflows. Focus on bridging experimentation and production using Databricks and Azure to create practical business value.

Location: Hybrid (Katowice HUB, Poland)

Company

LIPTON Teas & Infusions is the world’s leading tea business, home to iconic brands like Lipton, Pukka, Tazo, T2, Lyons, and PG Tips.

What you will do

• Build and maintain ML pipelines for training, inference, evaluation, and data preparation.
• Develop solutions for computer vision, forecasting, classification, and anomaly-related workflows.
• Integrate LLMs into pipelines and workflow steps to generate practical business value.
• Build and maintain supporting APIs, jobs, and orchestration layers for ML-enabled applications.
• Use Databricks and AzureML to manage environments, runs, data pipelines, and deployment paths.
• Ensure engineering quality through version control, CI/CD, testing, packaging, and containerization.

Requirements

• 2-4 years of experience in ML engineering, data science, or software engineering.
• Bachelor’s degree in Computer Science, Software Engineering, Data Science, Mathematics, or a related field.
• Strong proficiency in Python, Azure, and Databricks.
• Working knowledge of PySpark, SQL, Git, and GitHub Actions.
• Experience productionizing ML workflows beyond notebook-only experimentation.
• Location: Must be based in or able to work in a hybrid setup at the Katowice HUB, Poland.

Nice to have

• Experience with AzureML or MLflow.
• Knowledge of FastAPI, React, or TypeScript.
• MLOps experience.

Culture & Benefits

• Yearly salary review and annual performance-based bonus.
• Private medical care and employer-paid life insurance.
• Monthly MyBenefit cafeteria points and holiday reimbursement.
• Access to discounted company products and employee referral rewards.
• Structured onboarding and continuous learning opportunities.
• Collaborative environment with cross-functional global teams.

Hiring process

• Usually consists of 2-3 stages.
• CV review is typically completed within 2 weeks.