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Data Scientist / Machine Learning Engineer

Discussion

What You would do at KPMG:

  • collaborating on the design and development of ML‑based applications and their backend components
  • helping to select the most applicable solutions for a given business problem
  • writing clean, efficient and well‑documented code
  • contributing to our MLOps processes
  • staying up to date with emerging trends and technologies in software development

What brings you aboard:

  • a completed Master’s degree (ideally in Statistics, Mathematics or Computer Science) or up to 3 years of relevant work experience
  • proven experience using Python and basic knowledge of shell scripting
  • familiarity with software development methods and version control tools such as Git
  • ability to work independently and reliably in a small team
  • proactivity and eagerness to learn
  • willingness to experiment with various generative and descriptive AI use cases
  • at least intermediate proficiency in English (oral and written); Hungarian knowledge is an advantage

What we believe in and do jointly with You:

  • experience with database technologies (MS SQL, PostgreSQL, MongoDB)
  • experience with deep learning models and related Python packages such as Transformers or PyTorch
  • experience in developing NLP models
  • experience with Azure

What we offer:

  • competitive salary and a wide range of cafeteria elements
  • private health insurance, life and accident insurance
  • company laptop and iPhone to support efficient work
  • employee wellbeing programs: discounted gym membership and other sports opportunities
  • diverse projects and experience with up-to-date technologies
  • structured onboarding and mentoring program
  • transparent and dynamic career path (annual promotion opportunities)
  • profession and personal growth via professional mentoring and several online and offline learning opportunities
  • a close-knit, cohesive teams where members help one another to achieve a common goal
  • hybrid and flexible working arrangements
  • opportunity to participate in volunteer activities throughout the year, with additional paid leave provided
  • active community life and regular team‑building events

See also

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