Junior Machine Learning Engineer (RAG Agents)

Required skills:

• Strong theoretical background in machine learning and neural networks.
• Knowledge of Python and machine learning libraries (PyTorch, TensorFlow, scikit-learn).
• Experience with large language models (GPT, BERT, or similar).
• Ability to understand existing processes and identify areas where ML can be applied to optimize them.
• Basic skills in process automation tools (e.g., n8n, Zapier).
• Proactive attitude, with a willingness to take responsibility for experiments and research.

As a plus:

• Experience with RAG frameworks (Haystack, LangChain, etc.).
• Skills in working with APIs to integrate solutions into existing systems.
• Understanding of DevOps principles (containerization, CI/CD).
• Experience in designing ETL processes.
• Experience with cloud platforms (AWS, GCP, Azure).

Responsibilities:

• Research and implement Retrieval-Augmented Generation (RAG) agents to automate document analysis and management.
• Set up, train, and, if necessary, fine-tune large language models (LLMs) to address team tasks.
• Develop tools to simplify working with source code, such as auto-generating documentation, error detection, and assisting with refactoring.
• Participate in the design and optimization of new team processes based on ML solutions.
• Use workflow automation tools to integrate ML solutions into existing processes.
• Experiment with approaches and architectures, proposing ideas for improvements and their future implementation.
• Provide recommendations and create prototypes that will serve as the foundation for future workflows.

What company offers?

• The opportunity to play a key role in developing new team processes.
• Freedom for experiments and research that influence decision-making.
• Mentorship from experienced specialists, as well as collaboration in a creative and supportive team.
• Participation in projects where you can implement cutting-edge technologies and see their real impact.
• Access to modern tools and resources for learning and professional growth.
• Flexible schedule and the possibility to work remotely.

 

How to Apply: Interested candidates are encouraged to submit a resume or LinkedIn link to [email protected]

 

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