Medeina · Role guides · ML Engineer
ML Engineer: skills & learning path
Medeina maps what a ML Engineer role typically needs, then helps you plan books, courses, certifications, and interview prep against your own skills or CV.
Treat the list below as the usual baseline for this title. Seniority changes how deep each skill needs to go, not the names.
Typical requirements
Ranked by how often they show up for this kind of role.
- Machine Learning — importance 100%
- Python — importance 100%
- PyTorch — importance 75%
- TensorFlow — importance 60%
- SQL — importance 55%
- AWS — importance 50%
- Docker — importance 50%
Questions people ask
What skills does a ML Engineer need?
The skills that usually matter for a ML Engineer are Machine Learning, Python, PyTorch, TensorFlow, SQL, AWS, and Docker.
How do I learn ML Engineer skills?
Compare Machine Learning, Python, PyTorch, TensorFlow, SQL, AWS, and Docker with your CV on Medeina, then follow the books, courses, and interview prep it lines up for the gaps.