Machine Learning Engineer

AI overview

Develop intelligent assistant features using ML and NLP models, with a focus on agentic workflows and collaborative engineering efforts to enhance AI-powered tools.
  • Develop and integrate ML and NLP models to power intelligent assistant features 
  • Build agentic workflows using LangChain, LangGraph, or similar frameworks 
  • Prototype user interfaces and internal tools using Streamlit or Gradio 
  • Collaborate with the engineering and product teams to plan and deliver ML-driven features 
  • Work with Docker to manage development and runtime environments 
  • Use Git for version control and write clean, maintainable code 
  • Query structured data using SQL 
  • Contribute to model deployment and operations in a cloud environment (primarily Azure) 
  • Strong proficiency in Python 
  • Experience with agentic AI frameworks such as LangChain or LangGraph 
  • Solid understanding of machine learning and NLP fundamentals 
  • Hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow) 
  • Familiarity with prototyping tools such as Streamlit or Gradio 
  • Knowledge of engineering best practices: Git, Docker, cloud basics, and task estimation 
  • Practical knowledge of SQL 
  • Upper-Intermediate level of English (both written and spoken) 

 

WOULD BE A PLUS

  • Experience with other agentic or LLM orchestration tools 
  • Experience with MLOps or model deployment 
  • Comfortable working in Linux terminal environments 

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