The opportunity
We work across product, growth, and monetization to help people get more value from OpenAI’s products. We identify opportunities for machine learning, build and test early solutions, and partner with engineering and product to bring successful approaches into production.
What you'll do
Identify opportunities with product and business partners, define the: decision a model will inform, and prioritize work by user value, feasibility, and expected impact.
Build datasets, features, reproducible training workflows, and models. You’ll: use a combination of tools appropriate to the task at hand.
Translate predictions into product actions. Design experiments and use causal: reasoning to establish whether those actions improve user and business outcomes.
Partner with engineers on integration, serving or batch scoring, monitoring,: and rollout. Stay involved through launch and iteration.
Explain results and limitations clearly, document decisions, and build: reusable methods that other teams can adopt.
Have built and evaluated applied ML systems that influenced a product or: business decision, with clear ownership of the modeling work.
What they're looking for
- Write effective Python and SQL and can investigate imperfect data, debug: models, and make pragmatic implementation choices.
- Build and schedule production scoring pipelines using dbt, airflow, and flyte.
- Understand supervised learning, evaluation, experimentation, and the: difference between predicting an outcome and changing it.
- Can scope ambiguous problems, work across disciplines, and explain technical: tradeoffs to colleagues with different backgrounds.