Job description

For an international client, we are looking for a specialist for the position of Machine Learning Engineer.

The work takes place in an English-speaking environment.

We are looking for a passionate, high-energy, and proactive Machine Learning Engineer with proven previous experience in NLP and Computer Vision to enhance our Client’s Machine Learning/Deep Learning team. The team works on the AI platform which provides modern enterprises with solutions for processing large and complex documents.

The Client is a prominent intelligent automation software company that aims to make AI accessible for enterprises to streamline document-centric business processes. They work with a seasoned team of AI experts, comprising scientists, researchers, and engineers, to help companies address their organizational business challenges.


  • Models Building: Build, develop, and scale machine learning models that meet business and technical requirements.
  • Technical Advisory: Serve as the go-to technical expert in machine learning for both internal and client-facing presentations.
  • Code Review and Quality Assurance: Ensure that code and models meet quality and performance standards.
  • Project Management: Lead end-to-end machine learning projects involving client interactions, requirements gathering, timeline estimations and derivables.
  • Client Relationship Management: Maintain and enhance relationships with clients by providing excellent service and understanding client needs for machine learning applications.
  • Requirements Analysis: Collaborate with clients to understand business requirements and translate them into technical specifications.


  • Minimum 3 years of experience with Python and libraries such as Pandas, scikit-learn, PyTorch, Hugging Face, MMDetection, and MMClassification.
  • Knowledge of NLP, Computer Vision, and document information extraction.
  • Proven experience with data analysis, wrangling, and transformation.
  • Demonstrated experience in building, training, and optimizing deep learning models to resolve NLP task such as Token Classification and Text Classification using the Hugging Face library.
  • Demonstrated experience in training Computer Vision models for Image Classification, Object Detection and Segmentation.
  • Understanding of key machine learning concepts and metrics, such as F-measure.
  • Proficiency in using Google Colab and Weights & Biases for building and tracking ML experiments.
  • Familiarity with Git for version control.
  • Strong problem-solving skills, attention to detail, and ability to work independently and collaboratively.

Technologies We Use In Our Projects

  • architecture: Python (Pandas, scikit-learn, PyTorch, Hugging Face, MMDetection), Hugging Face,
  • data processing techniques: natural language processing (NLP), AI/machine learning (ML)


  • flexible working hours
  • conference and training budget
  • fitness card & private health insurance
  • remote model

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