Senior Machine Learning Engineer
Build the models and agents that read a plant's records and connect them, so scientists and engineers get answers they can check against the sources.
- Office
- Toronto
- Type
- Full-time
- Workplace
- Hybrid
- Pay
- $180,000 to $230,000 a year
About the role
Katalyze reads the records a medicine is made from: batch records, certificates of analysis, deviation records and the data around them. Much of it arrives as scanned pages, forms and tables. The models you build turn those pages into data the Context Layer can connect, and the agents on top of it retrieve, reason over and cite that material.
You'll also build the evaluations that tell us whether an answer is right before an expert sees it, working with domain experts to define what correct looks like. You'll own systems from prototype to production.
You'll work with the AI team and with deployment, close to the scientists and engineers who use what you ship. The role is based in our New York City office.
What you'll do
- Train and evaluate models that read scanned and digital manufacturing records
- Build the pipelines that turn each read into structured data with its source
- Measure accuracy on real documents and close the gaps you find
- Work with deployment on the records each customer brings
- Design agent workflows that retrieve, reason over and cite records across systems
- Build evaluation sets with domain experts and run them on every model change
- Improve accuracy, latency and cost, and mentor engineers on the AI team
What we look for
- Five or more years building machine learning systems in production
- Experience with document understanding, OCR or language models
- Strong Python, and the habit of measuring before changing
- Experience building retrieval systems and evaluation frameworks for LLM-based products
- A record of taking models from prototype to production and keeping them reliable
- Clear writing about trade-offs and care for the people who rely on the answers
Nice to have
- Experience in life sciences or another regulated industry
- Published work in document AI or information extraction
- Experience deploying models in on-premises or validated environments
Benefits
- Health insurance
- Great medical, dental and vision coverage.
- 401(k)
- Save for retirement with a 401(k).
- Hybrid work
- Work from our offices in New York City, Toronto or San Francisco, and from home.
- Equity
- Stock options, so you own a share of what we build.
- Flexible time off
- Time off when you need it.
- Equipment
- A new laptop and the setup you need.
Katalyze is an equal opportunity employer.
Senior Machine Learning Engineer
Toronto · Full-time · Hybrid