# Senior Machine Learning Engineer II, Ads Response Prediction at Instacart

- Company: Instacart
- What the company does: Order same-day delivery or pickup from more than 300 retailers and grocers. Download the Instacart app or start shopping online now with Instacart to get groceries, alcohol, home essentials, and more delivered to you in as fast as 1 hour or select curbside... Backed by General Catalyst, Khosla and Kleiner Perkins.
- Company website: https://www.instacart.com/
- Type: Startups (AI role)
- Level: Senior
- Location: United States - Remote
- Work setup: Remote
- Posted: 2026-05-28
- Apply by: 2026-10-12
- Apply: https://instacart.careers/job/?gh_jid=7963838
- Page: https://www.1752.vc/careers/jobs/instacart-senior-machine-learning-engineer-ii-ads-response-prediction/

## About the role

As a Senior Machine Learning Engineer II on the Ads Response Prediction team, you will lead the design and development of core ML models that power Instacart’s ads ecosystem. This is a research-leaning role focused on theoretical problem formulation, training methodology, and model quality rather than infrastructure or full-stack engineering.

## What they're looking for

- PhD/Master in machine learning, statistics, computer science, information retrieval, or a closely related quantitative field
- 6+ years of combined academic and industry experience (including PhD research) applying ML to ranking, recommendation, or prediction problems at scale
- Deep understanding of CTR/conversion prediction modeling, including familiarity with architectures such as Deep & Wide, DeepFM, DCN, and multi-task learning formulations
- Strong foundation in causal inference, counterfactual reasoning, and training data bias mitigation. Ability to reason about selection bias, position bias, and propensity-based correction methods
- Proficiency in Python and deep learning frameworks (PyTorch, Tensorflow, JAX). Fluency in data manipulation tools (SQL, Spark, Pandas)
- Track record of formulating ambiguous problems into well-scoped ML research directions and delivering results through rigorous experimentation

Tags: Machine Learning