Senior Machine Learning Engineer

2 tygodni temu

Warszawa, Mazovia, Polska Tidio Poland Sp. z.o.o. Pełny etat

At Tidio, we believe that AI will transform how businesses engage with their customers. As a leading provider of conversational chatbot solutions, we are at the forefront of this revolution. That's why we are looking for an exceptionally talented (Senior) Machine Learning Engineer to join our small but mighty Machine Learning team.

By joining the ML team as a (Senior) Machine Learning Engineer, you will become a crucial member of our 8-person team and help us push the boundaries of conversational AI. You will work closely with our talented engineers and product leaders to ideate, build, and refine industry-leading NLP models and algorithms that power our platform. This is a unique opportunity to turn your passion for machine learning into world-class products that deliver real value to the customers. You will provide state-of-the-art conversational AI products on a global level, reaching millions of consumers.

It is worth adding that we recently received an 10 million PLN grant to fine-tune generative open-source models on our data and replace external LLMs with our own.

Senior Machine Learning Engineer (NLP)

Your responsibilities

  • Be a part of a small team whose goal is to build tools on top of text data, to help in the automatic analysis of our client's problems.
  • Own and drive the full machine learning lifecycle from data preprocessing to model deployment, overcoming challenges in data pipelines, experimentation, and transitioning research into robust production-level systems.
  • Design, build, and refine machine learning models, particularly in NLP, to improve our chatbot's conversational abilities and language understanding.
  • Keep up-to-date with the latest research and techniques in deep learning and NLP.
  • Optimize infrastructure for machine learning production systems.
  • Monitor and analyze model performance in live environments and implement improvements.
  • Collaborate with product managers and engineering teams to identify and implement ML solutions for product features.

Our requirements

  • Have 4+ years of experience building NLP and deep learning models in industry settings.
  • Have expert knowledge in Python, PyTorch, and common ML frameworks.
  • Have strong software engineering skills and experience deploying models to production.
  • Have a strong passion and drive for self-development – following the latest trends and publications in the field of your specialization on an ongoing basis.
  • Have a team-player mindset.
  • Can communicate in English fluently.
  • At this point, asking about ownership, communication, and problem-solving skills seems like a rhetorical question, right?
  • MLOps experience.

What we offer

  • Salary up to PLN 33.000 under a B2B contract or an equivalent within the employment contract.
  • Work with an experienced team that continually shares knowledge and is not afraid of testing new solutions.
  • Remote-first work with flexible hours.
  • Possibility to use one of our offices in Poland or book a coworking space in your city.
  • Great development opportunities – company-supported courses and conferences.
  • 26 days off guaranteed in a year.
  • Individual work tools—MacBook Pro, Dell screen, JBL headphones? You can tailor the equipment to your needs
  • Sport & wellness benefit.
  • Private medical care.
  • Mental well-being program – individual therapy sessions and resources for employees.
  • Free access to one of the most popular e-book/audiobook services.
  • Regular social events (company-wide offsites, team events).
  • Budget for 1:1 English language classes.

Read this article, written by Bartek Kowalczuk, our Machine Learning Lead, on how we created Lyro – the first fully conversational AI chatbot for SMBs – in only 3 months >> https://bit.ly/3LvBd4E. Also, check our poster from ML in PL Conference 2022 >> https://bit.ly/3Rz0E9h, and articles about enhancing chatbot intent classification >> https://bit.ly/4gndikQ, and dataset expansion with pseudo-labeling >> https://bit.ly/3OI0gCw.

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