Senior Machine Learning Engineer II, Ads Response Prediction

🕒 vor 2 Monaten

🏄 California, Colorado, +17 weitere Bundesländer – Remote

🏄 California – Remote ⛰️ Colorado – Remote 🦌 Connecticut – Remote 🏛️ District of Columbia – Remote 🌺 Hawaii – Remote 🌽 Illinois – Remote 🦞 Maine – Remote 🗻 New Hampshire – Remote 🏖️ New Jersey – Remote 🗽 New York – Remote 🌲 Oregon – Remote 🦀 Maryland – Remote 🍂 Massachusetts – Remote 🔔 Pennsylvania – Remote ⚓ Rhode Island – Remote 🤠 Texas – Remote 🍁 Vermont – Remote ⚔️ Virginia – Remote ☕ Washington – Remote

💵 $201.000 - $253.500 / Jahr

⏰ Vollzeit

🟠 Senior

🤖 Machine-Learning-Entwickler

🦅 H1B-Visum-Sponsor

Dieses Unternehmen hat in der Vergangenheit H1B-Visa gesponsert.

Jetzt Bewerben

Ähnliche Remote-Jobs finden

E-Mail-Benachrichtigung für neue Jobs einrichten

📊 Überprüfen Sie Ihre Lebenslauf-Bewertung für diese Stelle

Verbessern Sie Ihre Chancen auf ein Vorstellungsgespräch, indem Sie Ihre Lebenslauf-Bewertung vor der Bewerbung überprüfen.

Lebenslauf hochladen

Instacart

WebsiteLinkedInAlle Stellen

1001 - 5000 Mitarbeiter

Gegründet 2012

🍽️ Lebensmittel & Getränke

📦 Logistik

🛍️ eCommerce

💰 €232.000.000 Venture Round im 2021-11

Food & Beverage • Logistics • eCommerce

Instacart ist ein Unternehmen, das einen flexiblen Arbeitsansatz bietet und gleichzeitig die Lebensmittelbranche transformiert. Es bietet einen wesentlichen Service, indem es Lebensmittel und Haushaltswaren in nur 30 Minuten bis an die Haustür der Kunden liefert. Instacart bietet persönlichen Einkäufern sichere und flexible Verdienstmöglichkeiten und adressiert Herausforderungen wie die Umleitung von Lieferungen während Schneestürmen und die Verbindung von Kunden mit Coupons und Angeboten. Es zielt darauf ab, das Betriebssystem für die Lebensmittelbranche zu sein und hilft damit Kunden, Zeit für andere Aktivitäten zu sparen. Instacart legt in seiner Unternehmenskultur Wert auf Vielfalt, Gerechtigkeit und Zugehörigkeit.

Beschreibung

• Lead 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 LoRA adaptors for scalable domain fine-tuning. • Drive sequence modeling initiatives including the TIGER generative retrieval system and Semantic ID representation learning, expanding their application across ads surfaces such as Product Details, Search and other placements. • Collaborate with the broader ML community in the company on the path toward Foundation Models using autoregressive user behavior prediction. • Formulate and scope ambiguous modeling problems from first principles. Translate business observations (e.g., overcalibration patterns, cold-start underperformance) into well-defined ML research directions with clear evaluation criteria. • Publish and present findings internally. Contribute to the team’s culture of technical rigor through design reviews, paper sharing, and experiment retrospectives.

🎯 Anforderungen

• 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. • Strong written and verbal communication skills. Ability to explain complex modeling decisions to cross-functional stakeholders including product managers and data scientists.

🏖️ Vorteile

• Highly market-competitive compensation • Eligible for a new hire equity grant • Annual refresh grants