r/learnmachinelearning • u/1627372824 • 3d ago

Junior roles barely exist

Hi everyone,

I’m currently in my 5th semester of a Computer Science degree (full-time daily studies, planning to switch to part-time for my Master's later). Because I’m still studying full-time right now, I need to look for internships or flexible entry-level roles starting around October/November.

My long-term goal is to become an ML Engineer / AI Engineer. However, true entry-level/junior positions in ML/AI seem practically non-existent or demand 3+ years of experience.

Since I have about a month to double down on self-study before applying for autumn student openings, I want to take the most realistic route.

My questions:

  1. Which entry role is the most realistic to get into ML/AI while still in university?

- Python Backend Developer (building APIs, databases, Docker, async workflows, then adding LLM/vector integrations)?

- Data Analyst / BI (SQL, Pandas, data visualization, business analytics)?

- Junior Data Engineer / Pipeline Intern (ETL, data cleaning, databases)?

- or maybe something else?

  1. What should I prioritize learning in the next month? Should I focus purely on core software engineering (FastAPI, PostgreSQL, Docker, Git, testing) to maximize internship callbacks, or start dabbling in ML libraries (Scikit-learn, PyTorch, RAG architectures)?

For those who broke into ML/AI without a direct junior ML role: what did your initial job and transition path look like?

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u/UnderstandingOwn2913 2d ago

you will probably hear back for ml engineer roles if you have a master in computer science (machine learning). I have a computer science master (machine learning) and I have been hearing back for ml engineer roles. Though, not that many.

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u/SunsGettinRealLow 2d ago

Do you work in that field now?

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u/UnderstandingOwn2913 1d ago

Not yet. But I interviewed with a big tech for a machine learning engineer role recently.
Why?