Senior Machine Learning Engineer

About the Opportunity

Grubhub is looking for an innately curious, business‑minded, results‑oriented Data Scientist or Machine Learning Engineer to work in our Discovery and Foundation team. You will partner with other data scientists, engineering, and product to deliver new run‑time models and services, create metrics to validate performance, propose new algorithmic approaches, design A/B tests, and identify creative solutions to bridge state‑of‑the‑art information retrieval and business/engineering requirements.

Additionally, you will drive technology best practices and guide the evolution of responsive systems.

Some specific responsibilities include but are not limited to creating documentation accessible to both technical and non‑technical audiences, mentoring junior data scientists, creating and maintaining automated training jobs, creating metrics dashboards and alerts, and advising on best algorithmic trade‑offs to business stakeholders.

• Help the business gain insights from recommendations in search and discovery with regard to short and long‑term metrics
• Drive orders and diner returns via enticing and relevant recommendations for searches
• Bring state‑of‑the‑art advances in IR systems to our runtime environment; assess new algorithms and business policies
• Collaborate with Product and Engineering teams to understand new product ideas, assess risks, and ensure that the necessary data is available
• Discover new and innovative ways to refine what we're doing and question existing assumptions
• Relentlessly analyze and improve the performance of our business

• MS/PhD in a quantitative discipline (Computer Science, Math, Physics, Engineering, Statistics, or other technical field) or equivalent experience
• 4+ years of experience with data analytics, machine learning, or a related field
• 2+ years of experience in applied predictive modeling with Tensor Flow
• 2+ years of experience in information retrieval or recommendation systems
• Experience with language models, especially on imperfect grammars
• Experience with Large Language Models (LLMs), including fine‑tuning and deploying transformer‑based architectures in real‑world applications
• Experience tuning runtime models using GPUs
• Experience in data engineering and feature preparation in PySpark, Hive, and the Python data stack
• Comfort communicating performance metrics, model details, and features specifications to technical and non‑technical audiences
• Ability to keep up with the latest publications and synthesize research into working models
• Deep interest in self‑motivated continuous learning

Our hybrid model requires 3 days a week in the office. Many team members choose to come in more often to take advantage of in‑person collaboration and connection. You’re welcome—and encouraged—to be in the office up to 5 days a week if it works for you.

#LI-Hybrid

New York: $176,000 - $191,000 per year.
Illinois: $158,500 - $172,000 per year.

We offer a competitive salary package including equity and 401(k). Additionally, we provide multiple medical, dental, and vision plans, and many other benefits and perks that are not listed.

At Wonder, we build the best teams by hiring with an objective lens — evaluating people for their potential while championing diversity, equity, and inclusion. We do not discriminate based on race, color, religion, gender identity or expression, sexual orientation, national origin, age, military service eligibility, veteran status, marital status, disability, or any other protected class. As part of our commitment to fair and compliant hiring practices, Wonder participates in the federal government's E‑Verify program to confirm employment eligibility.

If you need an accommodation during the interview process, please let your recruiter know.