About this role

Contribute to building and improving ML pipelines, from data preparation to deployment.
Support the deployment and monitoring of models in production environments.
Collaborate with Data Scientists and Engineers to translate ideas into scalable solutions.
Assist in automating workflows across the ML lifecycle (training, evaluation, retraining).
Troubleshoot model or pipeline issues and help identify root causes.
Contribute to internal tools, APIs, and reusable ML components.
Participate in code reviews and team ceremonies in an Agile environment.
Learn and apply best practices in MLOps, cloud, and production engineering.

Foundational experience in machine learning, software engineering, or data engineering.
Working knowledge of Python and SQL, with an interest in writing clean, maintainable code.
Understanding of the ML lifecycle, from experimentation to production.
Familiarity with cloud platforms or strong willingness to learn (AWS, GCP, Azure, Databricks).
Exposure to tools like Git, Docker, or CI/CD pipelines.
Curious mindset with strong problem-solving ability.
Comfortable collaborating with cross-functional teams.
Strong communication skills and eagerness to learn from others.

Junior Machine Learning Engineer

Key skills