At Dscout, we’re building the most flexible and powerful UX research platform on the market—trusted by the world’s top brands in finance (JP Morgan Chase, Intuit, Charles Schwab, PayPal), healthcare (Aya, Headspace), consumer goods (Keen, Verizon, Target, Northface), and tech (Google, Amazon, Facebook, Meta, Spotify, AirBnB).
Our tools help teams deeply understand the humans behind their products, so they can build better ones.
We are expanding our smart and driven team and would love for you to join us.
AI is a core part of how Dscout operates.
Feature quality relies heavily on the data pipelines and infrastructure under the hood.
As an AI Data Engineer you will be at the intersection of ML systems and data engineering, working closely with our MLE and analytics engineering teams to build the pipelines, models, and evaluation systems that make our AI features trustworthy in production.
Dscout sits at a unique intersection: a platform where rich human behavior data meets the researchers trying to make sense of it.
Getting that data right: structured, trustworthy, and ready to power both AI features and the reporting researchers rely on is foundational work.
That's what this role is.
What you'll do Design, build, and own the data pipelines that move and transform data from our application and third-party sources into relational databases - keeping them reliable and well-modeled as volume and complexity grow Partner with analytics engineering to build the data models and reporting that give researchers and teams real visibility into how their work is performing Own data quality as a first-class concern across ingestion, modeling, and reporting.
Catch problems before they reach a model, a dashboard, or a user, and fix them Build and ship production AI systems the data infrastructure and services that ML features run on Design and own evaluation systems that tell us whether an AI feature is ready to ship and holding up over time: eval harnesses, test datasets,.