Senior Machine Learning Engineer, Ads Response Prediction

Instacart · Canada - Remote (ON, AB, BC, or NS Only)Remotesenior

In short

▸Ingeniero de ML senior que desarrolla modelos de predicción de clics (pCTR) para anuncios en Instacart.
▸Trabajas en problemas de sesgos en datos de entrenamiento, calibración de modelos y arquitecturas avanzadas como MoE y Transformers.
▸Destaca el enfoque en investigación y ciencia de modelos, no en infraestructura.

Proficiency in English required

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What they ask for

✓Experiencia sólida en modelado de pCTR y predicción de conversiones.
✓Conocimiento profundo de sesgos en datos (selección, posición, curse del optimizador).
✓Habilidades en técnicas de debiasing: IPW, MNS, minimización de riesgo contrafactual.
✓Experiencia con modelos multi-tarea y arquitecturas como MoE o Transformers.
✓Experiencia con modelos secuenciales y LLMs integrados en recomendaciones.
✓Capacidad para trabajar en un entorno de investigación y desarrollo centrado en modelos.

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

pCTR modelingconversion predictionselection biasposition biasoptimizer's cursemodel calibrationPlatt scalingisotonic regressionMixed Negative Sampling (MNS)Inverse Propensity Weighting (

Who should you write to at Instacart?

Your free dossier identifies the people who'd interview you — their background, what they value, and how to reach out so you stand out before applying.

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview As a Senior Machine Learning Engineer on the Ads Response Prediction team, you will own and execute the development of 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. You will work on meaningful challenges in pCTR modeling such as mitigating selection bias, position bias, and optimizer's curse in training data, improving model calibration across surfaces and domains, and advancing our multi-task learning and sequence modeling capabilities. You will contribute to our foundation model approach for ads ranking and work on cutting-edge retrieval systems like TIGER (Transformer Index for Generative Recommenders), Semantic ID and domain language models. The Ads Response Prediction team owns all systems, algorithms and ML models to ensure a relevant and engaging Ads experience to customers of all the platforms powered by Instacart. This includes search and exploration retrieval systems, sequential modeling and generative retrieval systems for next interaction recommendations, LLM integrations, relevance models, pCTR models, bidding models and incrementality models. The team optimizes for an efficient marketplace to ensure delightful customer shopping experience, desirable advertiser business outcome and Instacart Ads revenue. The team has strong ML infrastructure and MLOps support, including Delta/DBT-Spark data pipelines, Ray-based distributed training, and automated model deployment. This means you can focus your energy on advancing modeling science rather than building infrastructure. About the Job • Own and execute research and development of pCTR and conversion prediction models, with a focus on improving calibration, reducing training data biases (selection bias, position bias, optimizer's curse), and advancing model accuracy across Instacart's ads surfaces. • Design and implement debiasing techniques such as Mixed Negative Sampling (MNS), Inverse Propensity Weighting (IPW), counterfactual risk minimization, and calibration methods (Platt scaling, isotonic regression) to address systematic prediction biases. • Contribute to the next-generation Multi-Domain Multi-Task (MDMT) model architecture, incorporating innovations like Mixture-of-Experts (MoE), Transformer layers for sequential user behavior, and Lo

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