Machine Learning Scientist

5+ years building, evaluating, and deploying machine learning models in production environments.

Strong experience with modern deep learning frameworks and production ML workflows.

Experience building one or more of the following:

Experience designing experiments and using data to improve model performance in real-world product environments.

Experience with offline evaluation, A/B testing, counterfactual reasoning, causal inference, or other methods for measuring model impact.

Experience training, evaluating, tuning, and deploying machine learning models across deep learning and traditional ML approaches.

You’ll develop machine learning models that move beyond experimentation and into production, where they directly improve creator workflows and product experiences.

Working alongside Analytics, Product, and Engineering, you’ll help develop intelligent systems that improve how creators discover insights, make decisions, and create content.

Designing, training, evaluating, optimizing, and deploying production machine learning models.

Applying reinforcement learning, contextual bandits, online learning, and other adaptive learning approaches where they improve product outcomes.

Designing systems that balance exploration and exploitation, short-term performance and long-term value, and multiple competing product objectives.

Applying offline policy evaluation, counterfactual evaluation, causal inference, or related techniques to reason about model changes before and after deployment.