Senior Machine Learning Engineer

About the Role

We are looking for an experienced Senior Machine Learning Engineer to join a team responsible for developing and scaling production-grade machine learning solutions. In this role, you will drive the evolution of ML infrastructure, improve MLOps practices, and collaborate closely with data scientists to deliver reliable, scalable, and production-ready machine learning systems.

This is a senior, hands-on position that combines software engineering, machine learning, cloud technologies, and technical leadership. You will play a key role in designing ML architectures, optimizing deployment workflows, and mentoring other technical team members.

What You Will Do

• Design and enhance scalable machine learning architectures and production systems.
• Build and improve MLOps processes, including CI/CD pipelines, experiment tracking, model versioning, and monitoring.
• Collaborate with data scientists to deploy machine learning models into production while ensuring reliability, scalability, and maintainability.
• Develop and maintain Python-based services, ML infrastructure, and deployment pipelines.
• Provide technical guidance and mentorship to engineers and data scientists on software engineering and ML best practices.
• Work closely with cross-functional teams to translate business requirements into technical solutions.
• Evaluate and introduce new technologies that improve the efficiency and quality of machine learning platforms.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• 5+ years of professional experience as a Machine Learning Engineer or in a similar role.
• Strong experience designing and maintaining production machine learning systems.
• Excellent Python programming skills.
• Experience building and deploying machine learning solutions in cloud environments; AWS preferred.
• Hands-on experience with ML frameworks such as TensorFlow or PyTorch.
• Practical knowledge of MLOps tools and practices, including MLflow, GitLab CI/CD or similar CI/CD platforms, and model deployment and lifecycle management.
• Experience designing scalable data and ML pipelines.
• Ability to work closely with technical and non-technical stakeholders.
• Experience mentoring engineers or data scientists is highly desirable.
• Strong communication and collaboration skills.

Nice to Have

• Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Experience with AWS SageMaker.
• Knowledge of monitoring and observability tools such as Prometheus, Grafana, or Evidently AI.
• Experience with recommender systems or large-scale machine learning platforms.
• Passion for improving engineering standards, automation, and ML operational excellence.

Benefits

• Comprehensive benefits, including Udemy for Business, private medical care, Multisport card, veterinary package, language lessons, and shopping vouchers.
• Adaptable working hours and remote/hybrid work options.
• Professional development and learning opportunities, including perks related to official partnerships with Microsoft, AWS, Snowflake, Salesforce, and more.
• Collaboration with a diverse, international team.
• Forward-thinking and growth-oriented work environment.
• Team-building events, hackathons, and CSR initiatives.
• Annual company event in Mazury.
• Welcome pack.