Machine Learning Engineer

Senior level


Machine Learning Engineer with a focus on NLP

Work level

Senior level

Job types


Offer salary

We are seeking an experienced Machine Learning Engineer with a demonstrable track record of implementing successful machine learning solutions. The ideal candidate will have extensive experience with Large Language Models and NLP, showcasing the ability to tackle complex problems with innovative machine learning approaches.


  • Proven experience as a Machine Learning Engineer with a focus on NLP.
  • Solid understanding of machine learning and deep learning algorithms and their real-world advantages and limitations.
  • Strong familiarity with state-of-the-art machine learning models for NLP tasks.
  • Strong programming skills in Python.
  • Proficient in at least one of the following frameworks: PyTorch, TensorFlow.
  • Practical experience with ML and data-science libraries such as Scikit-learn. Pandas, Matplotlib.
  • Experience with version control systems (e.g., Git) and machine learning lifecycle management tools (e.g. MLflow, DVC).
  • Ability to write clean, maintainable, and efficient code.
  • Excellent problem-solving skills and willingness to think outside the box.
  • Outstanding collaboration and communication skills.

Preferred Qualifications:

  • Experience with cloud services (e.g., AWS, GCP, Azure) for deploying scalable ML solutions.
  • Practical knowledge of SQL, experience with both SQL and NoSQL databases
  • Knowledge of containerization (Docker).
  • Familiarity with continuous integration and deployment (CI/CD) practices.
  • Experience with optimization of machine learning models, e.g. quantization, knowledge distillation, Low-Rank Adaptation.
  • Experience with LLM prompt engineering and with frameworks that help building LLM based applications, e.g. LangChain or Guidance.
  • Experience with fine-tuning Large Language models.


  • Develop, train, and fine-tune Large Language Models for various NLP tasks, ensuring their effectiveness and efficiency in real-world applications.
  • Deploy machine learning models into production environments, ensuring their scalability, reliability, and seamless integration with existing systems.
  • Manage and optimize the entire data pipeline, including data collection, cleaning, and preprocessing, to prepare high-quality datasets.
  • Design, implement and evaluate precise and efficient prompts for Large Language Models.
  • Implement rigorous model testing and validation to ensure high-quality solutions.
  • Collaborate with cross-functional and truly multinational teams to integrate machine learning capabilities into the company’s products and services.
  • Keep up to date with the latest developments in the field and incorporate best practices into the real-world solution.
  • Mentor junior engineers and contribute to the team’s growth by sharing knowledge and expertise.

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