Mid ML Engineer: Document Intelligence on AWS & GenAI

externaljobboards; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Remote-friendly

International projects

Healthcare

Learning reimbursement

Job summary

externaljobboards is seeking a Middle Machine Learning Engineer to build document intelligence pipelines that extract structured data from large PDFs. The role sits at the intersection of applied ML, GenAI, and scalable AWS engineering, supporting a vehicle lifecycle platform for insurers, repair facilities, and parts suppliers.

You will design end-to-end pipelines on AWS, improve ML models for classification and extraction, handle PDFs up to 2000 pages, and work with subject matter experts to

Qualifications

• Strong Python experience with ML and data tools.
• Hands-on AWS ML and deployment tooling experience.
• Advanced SQL and data modeling skills.
• GenAI experience for document intelligence and production deployment.
• Experiment design, power analysis and hypothesis testing.
• Strong written and verbal communication for async remote work.

Responsibilities

• Design end-to-end document intelligence pipelines on AWS.
• Develop and optimize ML models for document classification and extraction.
• Build scalable data processing for PDFs up to ~2,000 pages.
• Collaborate with SMEs to refine extraction requirements.
• Take features from research to production and monitor performance.
• Establish evaluation frameworks and quality metrics for extraction accuracy.

Skills

Python

Pandas

Scikit-learn

TensorFlow

PyTorch

PyStats

Pydantic

SQL

Experiment design

GenAI concepts

English communication

Tools

AWS ML

SageMaker

Lambda

CloudFormation / CDK

Step Functions

AWS Bedrock / Azure OpenAI

Textract / Document AI tools

PyMuPDF / OpenCV / Pillow

Redshift / S3 / EMR / Glue

Job description

externaljobboards is seeking a Middle Machine Learning Engineer to build document intelligence pipelines that extract structured data from large PDFs. The role sits at the intersection of applied ML, GenAI, and scalable AWS engineering, supporting a vehicle lifecycle platform for insurers, repair facilities, and parts suppliers.

You will design end-to-end pipelines on AWS, improve ML models for classification and extraction, handle PDFs up to 2000 pages, and work with subject matter experts to