Senior Machine Learning Engineer

Description

The company is an AI-first global tech firm with 25+ years of engineering leadership, 2,000+ people, and 500+ active projects for Fortune 500 clients such as HBO, Microsoft, Google, and Starbucks.

It works with enterprise leaders on AI platforms and digital transformation.

The team is ambitious, collaborative, and keeps learning.

The client is the leading provider of vehicle lifecycle solutions, headquartered in Chicago. Its platform offers mobile, AI, and automotive technology and links 350+ insurance companies, 24,000+ repair facilities, hundreds of parts suppliers, and dozens of third-party data and service providers. It helps companies that build, insure, and replace vehicles work more productively and serve end consumers better.

Responsibilities

• Build document intelligence pipelines from start to finish on AWS.
• Create and tune ML models that classify documents, split them into sections, and extract fields.
• Engineer data processing systems that can handle PDFs of up to 2,000 pages.
• Work with subject matter experts to shape and sharpen extraction requirements.
• Take features from early research through release and ongoing monitoring.
• Define evaluation methods and quality measures for extraction accuracy.

Requirements

• Strong Python skills, including native Python plus Pandas, scikit-learn, TensorFlow or PyTorch, PyStats, and Pydantic.
• Hands-on work with AWS ML and deployment services such as SageMaker, Lambda, CloudFormation or CDK, and Step Functions.
• Advanced SQL and data modeling skills.
• Experience with GenAI for document work: prompt engineering, RAG, vision-plus-text multimodal models, and production deployment with AWS Bedrock or Azure OpenAI APIs.
• Experience designing experiments, including power analysis and hypothesis testing.
• Clear written and spoken communication, needed for a remote, largely asynchronous team.
• Ability to explain complex technical problems concisely and propose iterative solutions.
• Experience taking a feature from concept to production, covering proposal, discussion, and delivery.
• Experience with document processing tools such as AWS Textract, Azure Document Intelligence, or similar OCR and layout detection systems.
• Experience with PDF and image processing libraries such as PyMuPDF, OpenCV, and Pillow.
• Background in machine learning or data science: algorithm selection, feature engineering, model training, hyperparameter tuning, supervised and unsupervised learning, model pipelines, and ML frameworks.
• Experience with AWS big data services such as Redshift, S3, EMR, and Glue.
• English at upper-intermediate level.

Conditions

Remote work with a largely asynchronous setup.