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

• ▹Advanced knowledge of Python: native, Pandas, ScikitLearn, 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, production deployment using AWS Bedrock or Azure OpenAI
• ▹Experience in experiment design: power analysis and hypothesis testing
• ▹Proficiency in written and verbal communication for a remote, largely asynchronous work environment
• ▹Demonstrated capacity to own a feature from concept to production

Nice to have

• ▹Document processing tools: AWS Textract, Azure Document Intelligence, or similar OCR/layout detection systems
• ▹PDF and image processing libraries: PyMuPDF, OpenCV, Pillow
• ▹Machine learning / data science experience: algorithm selection, feature engineering, model training, hyperparameter tuning, supervised and unsupervised learning, 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 leadership, 2,000+ team members, and 500+ active projects for Fortune 500 clients including HBO, Microsoft, Google, and Starbucks. The client is the leading provider of vehicle lifecycle solutions, headquartered in Chicago, connecting 350+ insurance companies and 24,000+ repair facilities.