Intern Machine Learning Engineer


A Machine Learning Engineer is a specialist who effectively combines data analysis skills typically associated with the role of a Data Scientist with programming and software deployment skills typical of a Software Engineer. They build and design autonomous machine learning systems capable of processing large amounts of data and integrating with other software.

Their role is to work at the intersection of Data Science and software engineering – ensuring that ML models and algorithms are effectively implemented and optimized within larger systems, ensuring their performance, scalability, and above all, business value. They deal with all aspects of the ML model lifecycle, from conception, through development phase, to deployment and monitoring in production. In short – they are more “technical” than a Data Scientist, and more “analytical” than a regular software engineer.

Who are we looking for?

It would be great if you’re a final year student of engineering or master’s studies in fields such as Computer Science, Data Analysis and Processing, Data Science, Data Engineering, Mathematics, so that after completing the internship, working at least 4/5 of the full-time would be possible for you. We value proficiency in Python, and any personal or academic project experiences, participation in training sessions or competitions in the field of machine learning are highly appreciated.

Technology stack:

  • Programming languages: Python (required).
  • Version control systems: Git (required).
  • Cloud solutions: AWS, Azure, Google Cloud (basic knowledge of one of the mentioned solutions required).
  • ML/DL: Scikit-learn, Pandas, XGboost, LightGBM, PyTorch, TensorFlow, Keras (proficiency in at least one of the mentioned tools required).
  • Basic knowledge of machine learning (required).
  • Good knowledge of software engineering (required).

Nice to have:

  • MLOps: managing the ML model lifecycle.
  • Model monitoring: MLflow, Neptune.
  • Design patterns, code smells, continuous integration, code review, unit / functional / regression tests, databases, operating systems, computer networks, Flask, containers (Docker). helps companies discover the potential of their data and use it to build competitive advantage in the most effective way.

Our support covers all stages of the AI journey, from a feasibility study through to end‐to‐end AI solution development, deployment and maintenance. We follow methodology developed on the basis of research and commercial projects delivered for clients such as NTT, Nielsen, L’Oreal, Google and Intel.

Some of our benefits

Flexible working hours
Lunch provided
Onsite English Lessons
Kitchens stocked with fruit and veggies twice a week
Theatre discount
Monthly integration budget
Company library
Knowledge sharing via deeptalks project
Holiday celebration

Contact us

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  •, Inc.
  • 2100 Geng Road, Suite 210
  • Palo Alto, CA 94303
  • United States of America
  • Sp. z o.o.
  • al. Jerozolimskie 44
  • 00-024 Warsaw
  • Poland
  • ul. Łęczycka 59
  • 85-737 Bydgoszcz
  • Poland
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