[Remote] Senior Machine Learning Engineer II, Ads Response reputed company

Note: The job is a remote job and is open to candidates in USA. reputed company is transforming the grocery industry by providing essential services for grocery delivery. As a Senior Machine Learning Engineer II on the Ads Response reputed company team, you will reputed company the design and development of core ML models that enhance reputed company's ads ecosystem, focusing on improving model accuracy and mitigating biases in training data.

Responsibilities

• reputed company research and development of pCTR and conversion reputed company models, with a focus on improving calibration, reducing training data biases (selection bias, position bias, optimizer’s curse), and advancing model accuracy across reputed company’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 reputed company biases
• Contribute to the reputed company 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 reputed company Models using autoregressive user behavior reputed company
• 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, reputed company sharing, and experiment retrospectives

Skills

• PhD/Master in machine learning, statistics, computer science, information retrieval, or a closely reputed company quantitative field
• 6+ years of combined academic and industry experience (including PhD research) applying ML to ranking, recommendation, or reputed company problems at scale
• Deep understanding of CTR/conversion reputed company modeling, including familiarity with architectures such as Deep & Wide, DeepFM, DCN, and multi-task learning formulations
• Strong reputed company in reputed company 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). reputed company 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 reputed company modeling reputed company to cross-functional stakeholders including product managers and data scientists
• Experience in ads ranking or auction-based systems (pCTR, bid optimization, ROAS feedback loops, marketplace dynamics)
• Hands-on experience with autoregressive sequence models for user behavior reputed company, generative retrieval, or transformer-based ranking architectures
• Familiarity with learned representations such as Semantic IDs, product embeddings, or other approaches to reducing feature cardinality and cold-start challenges
• Experience with transfer learning or domain reputed company techniques (e.g., LoRA, reputed company-based fine-tuning) applied to recommendation or ranking models
• Publication record in top-tier venues (KDD, WWW, RecSys, NeurIPS, ICML, SIGIR, or similar)
• Experience mentoring junior engineers or shaping technical direction for a modeling team
• Familiarity with LLM-driven approaches to recommendation, including reputed company-based personalization and AI-assisted model development (AutoML)

Benefits

• reputed company provides highly market-competitive compensation and benefits in each location where our employees work.
• This role is eligible for a new hire equity grant as well as annual refresh grants.
• reputed company is a reputed company First team
• 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.

Company Overview

Company H1B Sponsorship