About the job
Wisedocs is an innovative and rapidly expanding AI platform that revolutionizes the way insurance companies evaluate claims. With approximately $20 million USD in funding, over 100 team members worldwide, and more than 90 clients across North America and Australia, we are experiencing remarkable growth, doubling our revenue year after year.
Founded by industry experts who have firsthand experience with the claims process, Wisedocs merges extensive domain expertise with cutting-edge AI, trained on over 100 million documents. Our platform simplifies complex medical records into clear, structured insights, supported by expert human oversight.
Join our mission-driven team dedicated to developing intelligent products that simplify complexity, expedite decision-making, and create a significant impact when it matters most.
Role Overview
We are on the lookout for a Senior Machine Learning Engineer to spearhead the scaling and innovation of machine learning initiatives across the organization. In this pivotal role, you will enhance our inference and training pipelines to accommodate a higher volume of customers while refining extraction and summarization techniques across various modalities. You will foster a customer-centric approach and collaborate with fellow senior engineers to seamlessly integrate the ML system into the broader Wisedocs platform.
Our Current ML Ecosystem
We have three primary types of ML systems operational in production: an entity classification system, a custom reports generator, and a series of summarization models. Our entity classification has been functioning for four years and currently processes data asynchronously using a combination of models. Discover more about our initiatives at our tech blog.
Recent Projects by Our ML Team:
- Reconstructing our inference pipeline to achieve 100x scaling
- Developing consistent parsing methods for 50,000-page PDFs
- Deploying our pipeline within an isolated government client environment
Your Responsibilities
- Designing and implementing machine learning models to analyze and interpret large sets of medical and insurance documents
- Creating robust, scalable APIs using Python
- Collaborating with technical stakeholders and leaders to contribute to system design and implementation
- Ensuring the reliability and scalability of ML systems while enforcing best practices in data engineering and model lifecycle management
- Working closely with our expert-in-the-loop teams to develop industry-leading evaluations
- Additional responsibilities will evolve as projects progress and change

