Machine Learning Engineer

Machine Learning Engineer

We want to do things differently, focusing on what truly matters. We return to our roots with a sustainable corporate strategy at our core. Work-life balance, beginner’s mind, and community involvement are our identity and our starting point for this journey.

Key Responsibilities

• Design, implement, and maintain the full machine learning lifecycle, including data preparation, feature engineering, model training, validation, deployment, and retraining.
• Ensure the operation, monitoring, and continuous improvement of research-ready and production-ready AI solutions through MLOps practices.
• Collaborate closely with Data Scientists and Data Engineers to define technical requirements and build scalable AI solutions.
• Develop and operationalize proof-of-concept and proof-of-value initiatives using state-of-the-art AI and machine learning frameworks.
• Support the deployment and maintenance of AI models in production environments, ensuring reliability, scalability, and performance.
• Promote knowledge sharing and contribute to the adoption of emerging AI technologies across the organization.
• Drive continuous improvements in machine learning engineering processes, tooling, and delivery practices.

Required Skills & Experience

• 3-5 years of proven experience in Machine Learning Engineering or related AI engineering roles.
• Strong programming skills in Python or similar languages used for Machine Learning development.
• Experience with Machine Learning frameworks such as TensorFlow , PyTorch , or Scikit-learn .
• Knowledge of data preparation, feature engineering, and model optimization techniques.
• Experience designing and implementing end-to-end machine learning solutions for research and production environments.
• Hands-on experience with model deployment, APIs, and MLOps practices.
• Familiarity with cloud-based AI platforms such as Azure ML , Snowflake , and dbt .
• Working knowledge of SQL and modern data pipelines.
• Experience training and refining AI models with business applications and measurable impact.
• Understanding of DevOps and MLOps principles for scalable AI solution delivery.
• Experience working collaboratively with Data Science and Data Engineering teams.

Nice to Have

• Experience implementing proof-of-concept and proof-of-value AI initiatives.
• Knowledge of Generative AI, Large Language Models (LLMs), and emerging AI technologies.
• Experience with cloud-native AI architectures and distributed computing environments.
• Strong critical thinking and attention to detail.
• Excellent collaboration and teamwork capabilities.
• Curiosity and commitment to continuous learning in AI and Machine Learning domains.
• Ability to manage multiple priorities and deliver results in dynamic environments.
• Strong verbal and written communication skills.
• Experience sharing knowledge and supporting AI adoption across engineering communities.

Machine Learning Engineer — Is that us?

• Horizontal structure. Everyone has a voice and is heard. We are looking for ambitious people who want to help us achieve what has not yet been done.
• Personalized support. We value close and regular follow-up. We are a team from day one.
• Comprehensive and flexible benefits package. Health insurance, life insurance, discounts and perks, telecommunications plan, and much more.
• Investment in learning and career development. Certified training, online learning platforms, Pearson VUE exam center… we invest in you!
• Sustainability and community involvement. We want meaningful work and to invest in an inclusive consulting project—and we need your help to make it happen.

Ready?

team.it, back to basics!

At Team IT, we stand for equality and value diversity. We create a safe and inclusive environment where opportunities are equal for everyone. We do not discriminate based on age, ethnicity, sexual orientation, gender, disability, or any factor other than merit. All applications from candidates with the right skills for the role are welcome.