All offersWrocławPythonSenior ML Engineer
Senior ML Engineer
Python
Olsys Ltd.

Senior ML Engineer

Olsys Ltd.
Wrocław
Type of work
Full-time
Experience
Senior
Employment Type
Any
Operating mode
Remote
Olsys Ltd.

Olsys Ltd.

OLSYS provides full-service solutions for mid-market and enterprise organizations. With 17+ years of experience, 100+ projects, and 200+ strong technical experts in the team, we continue to grow by expanding our development team in Europe, as well as expanding the base of new clients and projects. Our tailored approach, e-commerce focus, and flexible solutions allow us to design, develop, and deliver scalable, integrated commerce platforms that drive profits and boost the business.

Company profile

Tech stack

    NLP
    master
    Python 3
    advanced
    GPT
    advanced
    Microsoft SQL
    regular
    AWS
    regular
    LLM
    regular

Job description

Online interview

About the Company

OLSYS Ltd provides full-service solutions for mid-market and enterprise organizations.


As an enterprise software development company, we are building long term partnerships helping our clients accelerate their digital experiences with reasonable IT investments.

Our tailored approach, e-commerce focus, and flexible solutions allow us to design, develop, and deliver scalable, integrated commerce platforms that drive profits and boost the business.


15+ years of experience, 100+ projects, 50+ specialists


We are looking for an experienced Senior ML developer with 5+ years of experience.


About project: We are in the process of refactoring a huge monolithic application that has reached its limits in terms of scalability. Now we are moving with a split to microservices approach and moving to the cloud. Application is from the Compliance and Risk management domain. 


Current workstream

1. The project is an aggregator of various global regulatory content (requirements and standards in various industries). A special team collects content from all over the Internet and publishes it in our system. Then our team sends out emails about various updates in areas that are of interest to our customers. 


2. Now we are at the stage of moving from an on-prem data center to AWS. We are also developing Public APIs so that our customers can integrate with us. In the near future, we will be integrating with OneLogin to organize an SSO experience.


Requirements:

  • Experience with Large Language Models:
  • Proven experience working with large language models like GPT / Claude / Gemini
  • Familiarity with frameworks such as LangChain, Llama-index
  • Expertise in Natural Language Processing:
  • Strong background in NLP techniques such as text classification, sentiment analysis, named entity recognition
  • Experience with NLP libraries and frameworks (e.g., NLTK, spaCy, Hugging Face Transformers).
  • Programming Skills:
  • Proficient in Python and commonly used data science libraries (e.g., Pandas, NumPy, Scikit-learn).
  • Experience with deep learning frameworks like TensorFlow or PyTorch.
  • Familiar with SQL.
  • Experience with model deployment tools (e.g., Docker) and cloud platforms (e.g., AWS).


English: Upper intermediate


Responsibilities:

  • Developing and Training Models:
  • Design and implement pipelines using LLMs for generation of important insights from products regulation documents
  • Train NLP models to perform tasks as as classification of insights and documents
  • Data Collection and Preprocessing:
  • Collect, clean, and preprocess regulation data documents
  • Design data pipelines for efficient data manipulation and preprocessing.
  • Model Optimization and Tuning:
  • Fine-tune models and perform prompt engineering for better performance 
  • Optimize prompts to productionize the LLM pipeline
  • Model Deployment:
  • Deploy models into production environments, ensuring they are scalable, reliable, and secure.
  • Develop APIs to enable integration of models into business processes or products.
  • Performance Monitoring:
  • Monitor the performance of deployed models and make adjustments as necessary to maintain or enhance model accuracy and efficiency.
  • Collaboration with Stakeholders