Senior Machine Learning Engineer

Stack

Responsibilities

• ▹Design and implement end-to-end document intelligence pipelines on AWS
• ▹Develop and optimize ML models for document classification, segmentation and field extraction
• ▹Build scalable data processing systems handling PDFs up to 2000 pages
• ▹Collaborate with subject matter experts to create and refine extraction requirements
• ▹Own features from research through production deployment and monitoring
• ▹Establish evaluation frameworks and quality metrics for extraction accuracy

Requirements

• ▹Python experience (native, Pandas, Scikit-Learn, TensorFlow or PyTorch, PyStats, Pydantic)
• ▹Experience with AWS tools for ML engineering and deployment (SageMaker, Lambda, CloudFormation/CDK, Step Functions)
• ▹Advanced knowledge of SQL and data modeling
• ▹Experience with GenAI for document intelligence: prompt engineering, RAG, multi-modal models (vision + text), production deployment using AWS Bedrock or Azure OpenAI APIs
• ▹Experience in experiment design (power analysis and hypothesis testing)
• ▹Strong written and verbal communication for a remote, largely asynchronous environment
• ▹Ability to communicate complex technical problems clearly and propose iterative solutions
• ▹Experience owning a feature from concept to production

Nice to have

• ▹Experience with document processing tools (AWS Textract, Azure Document Intelligence or similar OCR/layout detection systems)
• ▹Experience with PDF and image processing libraries (PyMuPDF, OpenCV, Pillow)
• ▹Machine learning / data science experience (algorithm selection, feature engineering, model training, hyperparameter tuning, building model pipelines)
• ▹Experience with AWS big data technologies (Redshift, S3, EMR, Glue)

Soft skills

About the company

Exadel is an AI-first global tech company with 25+ years of engineering experience, 2,000+ team members and 500+ active projects. The client is a Chicago-based vehicle lifecycle solutions provider connecting insurers, repair facilities and parts suppliers.