Senior Machine Learning Engineer

This is an applied machine learning position with a heavy focus on engineering and not a research role. The expectation is that the candidate will be driving the development of our ML Ops and ML Engineering capabilities, as well as doing modeling work. We value short iterations that deliver value to our customers.

Take projects from ideation to production, including feature engineering, model construction, deployment, and model observability and evaluation.
Have access to and work with Large Language Models.
Help define our data roadmap. Which problems are amenable to AI/ML techniques, and which are better solved via simpler non-statistical methods? How might we define and evaluate data and model quality? Which models and techniques are best suited to our domain? You'll collaborate with our product and engineering teams to help answer these questions and more.
Collaborate with the rest of our data pipeline and ML engineering teams to build robust, high-scale systems that underlie all of our data processing and ML Operations.

You have 6+ years of experience in software engineering and/or Machine Learning, with at least 4 years of experience with applied machine learning in production, focused on ML Engineering and ML Ops.
You have 2+ years of experience with NLP techniques.
Experience with live A/B testing at scale.
You are a builder and care deeply about building systems and products that deliver meaningful value to users quickly and iteratively.
You have experience working with large, multi-terabyte datasets, and are comfortable with tools for high-scale data ingestion, transformation, analysis, and prediction.
You're excited to work collaboratively within engineering and across functional teams.
You’re eager to contribute your ideas and experiences to help Affinity continuously improve as a product and as a company.