Senior Machine Learning Engineer

Wisedocs is a fast-growing, venture-backed AI platform that transforms how insurance companies analyze claims. With ~$20M USD raised, 100+ team members globally, and 90+ customers across North America and Australia, we’re doubling revenue year over year.

Founded by experts who’ve experienced the claims process firsthand, Wisedocs combines deep domain knowledge with next-gen AI trained on 100M+ documents. Our platform turns complex medical records into clear, structured insights—backed by expert human oversight.

Join a mission-driven team building intelligent products that cut through complexity, accelerate decision-making, and make a real impact when it matters most.

We’re seeking a Senior ML Engineer to lead the scaling and innovation of organization-wide machine learning initiatives. In this role, you’ll scale our inference and training pipelines to fine-tune and serve higher volumes of customers, while improving extraction and summarization techniques across multiple modalities. You’ll build a customer-focused mindset and collaborate with other senior engineers to integrate the ML system into the broader Wisedocs platform.

We currently have three types of ML systems running in production: an entity classification system, a Custom Reports Generator, and a set of Summarization models. Our entity classification has been in production for 4 years and currently processes data asynchronously with a combination of models. You can read more about our work at https://(Use the "Apply for this Job" box below).-blog

• Rebuild our inference pipeline for 100x scale
• Figure out how to consistently parse 50k page pdfs
• Deploy our pipeline into an isolated government client environment

• Designing and implementing machine learning models to analyse and interpret large datasets of medical and insurance documents
• Developing robust, scalable APIs in Python
• Collaborating with other technical stakeholders and leaders to actively work towards the design and implementation of systems
• Ensuring the reliability and scalability of ML systems, implementing best practices in data engineering and model lifecycle management
• Work with our expert in the loop teams to build industry leading evaluations
• Other duties and responsibilities will be assigned as projects develop, adjust and mature

• Experience working across multiple engineering teams to deliver projects
• Technical excellence in one area of Machine Learning
• Strengths in one of backend engineering, data engineering or cloud engineering
• Ability to think through problems end to end, including data, infrastructure, research, monitoring and inference considerations
• Possess professional working experience with LLMs, RAG, BERT based models
• A track record of developing high-quality, maintainable code
• Excellent problem-solving skills in an independent and team setting
• Are enthusiastic about working in a fast-paced, innovative environment, contributing to a team that aims to make a significant impact in the medical and insurance tech space

• Flexible hybrid environment with the option to collaborate in-person at our Toronto HQ
• Modern employee benefits, including health and dental coverage
• Competitive compensation, with valuable stock options, as we’re still a young company growing very quickly
• An opportunity to develop very rapidly in your career. We can offer you a super-immersive learning environment, and when you thrive there, you will have the opportunity to rapidly develop this opportunity into senior practitioner or management opportunities as you choose
• Access to a learning and professional development fund to help you level up your career while you’re working with us. We hope to be an incredible step up in your career if you decide to come and work with us
• Company events
• Generous Paid Time Off
• Paid Sick Days
• Casual Dress code
• Employee Referral Bonus
• Tuition Assistance
• Plus, many other Recognition Programs

• Round 1 – People & Culture Chat: 20–30 min conversation about your background, goals, and the role.
• Round 2 – 1st Technical Assessment:
  An hour technical assessment that…