About the OpportunityGrubhub is looking for an innately curious, business-minded, results-oriented Data Scientist or Machine Learning Engineer to work in our Discovery and Foundation team. We are focused on providing high quality recommendations to diners who are exploring restaurants in their area as well as those who are searching for something specific. We also build models and features that characterize our merchant and menu item corpus. As a member of this highly collaborative team you will partner with other data scientists, engineering, and product to deliver new run time models and services. You will be responsible for creating metrics to validate performance of models, proposing new algorithmic approaches to improve our current system, designing A/B tests, and identifying creative solutions to bridge state of the art information retrieval advanced and business and engineering requirements. Additionally you will be driving technology best practices and guiding 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, advising best algorithmic trade offs to business stakeholders.
Our team practices end to end project ownership and our work focuses heavily on personalized recommendation and classification from content and clickstream. Deep neural networks, transfer learning from pretrained large scale models, classic regressions, fine tuning, and large language models all have a place in our daily lexicon.
The Impact You Will Make- 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.
What You Bring to the Table- MS/PhD in quantitative discipline (Computer Science, Math, Physics, Engineering, Statistics or other technical field etc) or equivalent experience
- 4+ years experience with data analytics, machine learning, or related field
- 2+ years experience in applied predictive modeling with TensorFlow
- 2+ years 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. That said, 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.
Wonder uses geographic-specific salary structures, which means the salary offered may vary depending on where the job is located. The final salary offer will take into account various factors, such as the candidate's skills, education, training, credentials, and experience.
BenefitsWe offer a competitive salary package including equity and 401K. Additionally, we provide multiple medical, dental, and vision plans to meet all of our employees' needs as well as many benefits and perks that are not listed.
A Final Note 
