Machine Learning Engineer

Objective: Develop, deploy and maintain ML models that solve unique customer problems.

Responsibilities

• Develop and maintain machine learning models using Python and scikit-learn, primarily regression and tree-based models.
• Work closely with product and data teams to understand business problems and translate them into data-driven solutions.
• Prepare, clean, and analyze data to ensure high-quality model inputs.
• Validate model performance and ensure reproducibility of results.
• Deploy ML models into production environments and monitor their performance over time.
• Collaborate with engineering and DevOps teams to integrate ML pipelines into production systems.
• Maintain and improve existing ML workflows using MLOps best practices (versioning, automation, CI/CD, monitoring).
• Write clear documentation and participate in code reviews to ensure code quality and maintainability.

Required Skills and Qualifications

• 2+ years of hands-on experience in applied machine learning or data science.
• Proficiency in Python and solid experience with scikit-learn.
• Good understanding of classical ML algorithms: linear/logistic regression, decision trees, random forests, etc.
• Experience with data wrangling and analysis using pandas and NumPy.
• Familiarity with version control tools (e.g., Git) and collaborative development workflows.
• Practical experience deploying ML models into production (e.g., APIs, batch pipelines, or cloud-based deployments).
• Basic understanding of MLOps practices, such as model versioning, CI/CD for ML, and model monitoring.
• Familiarity with containerization (e.g., Docker) and cloud platforms (e.g., AWS, GCP, or Azure) is a plus.
• Strong communication skills and ability to work collaboratively in a cross-functional team environment.

What do we offer:

• The opportunity to work with a diverse and talented team in a dynamic and innovative environment.
• Competitive salary and benefits package.
• A collaborative culture that values creativity, initiative, and continuous learning.
• Work on cutting-edge hotel automation technologies to enhance the future of hospitality.
• Collaborate with top hotel brands and technology providers in a fast-evolving industry.
• Company events, refreshments at the workplace.
• Additional week of vacation and 3 sick days.
• Work arrangement: Hybrid ( partially remote) possible.

Start date: 01.09.2025