ML Engineer

• Professional experience in AI Engineering or a closely related role.
• Strong Python skills and practical experience developing AI-powered solutions.
• Hands-on experience with Microsoft Azure in an AI or data context.
• Knowledge of software deployment, CI/CD, and monitoring practices.
• Ability to work effectively with project stakeholders and within a delivery team.
• Good communication, problem-solving, and documentation skills.

Nice to have:

• Experience with machine learning models, frameworks, and libraries.
• Practical knowledge of MLOps, including model deployment and monitoring.

• Learning & development opportunities – after your probation period, you’ll have access to a highly flexible and generous English language reimbursement program, along with an individual development budget to use as you see fit.
• Classic benefits like private medical care, a sports card, and a preferential life insurance plan. Plus, our infamous Fruit Tuesdays and Wednesdays.
• A hybrid work setup with plenty of flexibility. Delivery teams work mostly remotely. Enabling functions teams come to the office at least once a week. As an HR team, we meet every Wednesday. On the remaining days, you can choose where you work.
• A bunch of non-work activities, including Office Day (a fun-filled day when employees from all over Poland gather at the office), POP UP integrations, various competitions from cooking to photography, and the chance to submit charity causes to our CF4GOOD program, which provides support to those in need.
• A workplace that values people and is built on collaboration, not competition. If you’re tired of toxic work environments, you’ll finally get a chance to breathe. And if you’ve been lucky with great employers so far, we’ll do our best to keep that streak going.

,[Design, develop, test, and deploy AI-powered solutions., Build and maintain scalable AI solutions in Microsoft Azure., Use Python for AI solution development, automation, and integration., Apply best practices for deploying, maintaining, and monitoring AI solutions., Collaborate with data engineers, software engineers, and project stakeholders to translate business requirements into production-ready solutions., Create and maintain technical documentation related to AI solutions and delivered projects.] Requirements: Python, Azure, MLOps, PyTorch, scikit-learn, ML