Machine Learning Engineer III

Role Purpose

The Machine Learning Engineer III will play a critical role in advancing the Extraction teams mission to develop and enhance state-of-the-art solutions for large-scale data extraction. This role focuses on applying advanced machine learning and deep learning techniques to build secure, reliable, and high-performance systems that process complex visual and textual data, contributing to scalable and robust AI-driven platforms.

Role Value

As a Machine Learning Engineer III, you will have the opportunity to make a significant impact on the quality, scalability, and reliability of data extraction solutions. Your expertise in machine learning, deep learning, and computer vision will drive the development of innovative algorithms and production-ready models. By deploying and maintaining these solutions in real-world environments, you will support business-critical use cases across industries such as Financial Services, Travel, Fintech, Gaming, and the Sharing Economy, ensuring high standards of performance and user experience at scale.

Example Responsibilities

• Design and implement machine learning, deep learning, classical computer vision, and NLP algorithms focused on data extraction.
  
• Conduct research to support the development and deployment of advanced algorithms.
  
• Develop, evolve, and support production-quality code.
  
• Deploy models as AWS SageMaker endpoints or directly onto devices.
  
• Stay current with advancements in deep learning, computer vision, and NLP through academic research and industry conferences.
  
• Collaborate closely with engineers and product managers in an Agile development environment.
  

Experience and Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
  
• Minimum of 6+ years of commercial experience in computer vision, machine learning, or related areas (5 years with a Master’s degree), excluding academic study time.
  
• Strong proficiency in computer vision, deep learning, and natural language processing techniques.
  
• Experience working with Large Language Models (LLMs) and Vision Language Models (VLMs).
  
• Hands-on experience with PyTorch or TensorFlow, OpenCV, scikit-learn, and production-grade Python development.
  
• Proven experience implementing best practices for monitoring and maintaining ML models in production.
  
• Experience building, training, and deploying ML models in production environments.
  
• Strong communication and problem-solving skills.
  

Nice to Have

• PhD in Computer Science or a related field with specialization in computer vision, deep learning, or NLP.
  
• Experience developing algorithms for OCR, text extraction, and text understanding.
  
• End-to-end experience (training, deployment, monitoring) with VLM and LLM models in production.
  
• Understanding of Spring / Java-based system architectures.
  
• Experience working with cloud platforms such as AWS or GCP.