Senior/Lead Machine Learning Engineer

<p>We are looking for a Senior/Lead ML Engineer to join us at Exadel. This role works closely with data scientists, software engineers, and subject matter experts in different business areas to build production systems capable of processing multi-document PDFs, with automated document type detection and field extraction at scale.</p> <h3>Why Join Exadel</h3> <p>We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.</p> <p>From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.</p> <p>What powers it all? Our people are ambitious, collaborative, and constantly evolving.</p> <h3>About the Client  </h3> <p>The leading provider of vehicle lifecycle solutions, with headquarters in Chicago, enables the companies that build, insure, and replace vehicles to power the next generation of transportation. Its platform delivers advanced mobile, artificial intelligence, and car technologies. It connects a network of 350+ insurance companies, 24,000+ repair facilities, hundreds of parts suppliers, and dozens of third-party data and service providers. The customer's collective solutions enhance productivity and help clients deliver better experiences for end consumers.</p> <h3>What You’ll Do</h3> <ul> <li>Design and implement end-to-end document intelligence pipelines on AWS</li> <li>Develop and optimize ML models for document classification, segmentation, and field extraction</li> <li>Build scalable data processing systems handling PDFs up to 2000 pages</li> <li>Collaborate with subject matter experts to create and refine requirements for extraction</li> <li>Own features from research through production deployment and monitoring</li> <li>Establish evaluation frameworks and quality metrics for extraction accuracy</li> </ul> <h3>What You Bring</h3> <ul> <li>Advanced knowledge of Python (native, Pandas, ScikitLearn, Tensorflow or Pytorch, PyStats, Pydantic)</li> <li>Experience with AWS tools for ML Engineering and ML deployment (Sagemaker, Lambda, Cloudformation/CDK, Step Functions)</li> <li>Advanced knowledge of SQL and Data Modeling</li> <li>Experience with GenAI for document intelligence, including prompt engineering, RAG (Retrieval Augmented Generation), multi-modal models (vision + text), and production deployment using AWS Bedrock or Azure OpenAI APIs</li> <li>Experience in experiment design (power analysis and hypothesis testing)</li> <li>Proficiency in both written and verbal communication, required for a remote and largely asynchronous work environment</li> <li>Demonstrated capaci