Middle Machine Learning Engineer (Document Management System)

Requirements

• 3+ years of hands-on experience in ML, with a focus on NLP (text extraction & classification, anonymization and pseudonymization, document processing, clustering and other NLP tasks)
• Proficiency in Python
• Proven experience with LLMs APIs and/or open-weight models (e.g.: LLaMA, Mistral), with the use of frameworks like Langchain/Llamaindex for implementing solutions/features
• Proven experience with NLP techniques such as tokenization, stemming, lemmatization, and named entity recognition (NER)
• Experience with NLP libraries and frameworks like NLTK, spaCy, and Hugging Face Transformers
• Excellent communication skills for effective collaboration with cross-functional teams
• Strong problem-solving skills and ability to troubleshoot issues in model development and deployment
• At least an Upper-Intermediate level of English

Would be a plus

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field
• Experience with PoC development and prototyping in enterprise solutions
• Experience with LLM evaluation frameworks (e.g.: DeepEval, MLFlow, RAGAs, Deepchecks, etc.)
• Experience with fine-tuning open-source LLMs for domain and tasks
• Knowledge of MLOPs pipeline and instruments
• Familiarity with deep learning frameworks such as TensorFlow, PyTorch, or Keras
• Familiarity with the deployment of NLP models in production environments
• Knowledge of cloud platforms (AWS, Google Cloud, Azure) and their machine-learning services

Responsibilities

• Work under the supervision of the client’s research team to validate various ideas through PoCs, and to implement, train, test, and tune different learning models
• Collaborate with the research team to brainstorm and experiment with optimal models and open-source alternatives for NLP-based ideas to achieve the best possible results
• Apply best practices to effectively and securely implement pipelines for integrating models and ML-based solutions