Senior Machine Learning Engineer

Wonder•New York, NY

1d•$158,500 - $191,000•Hybrid

About The Position

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. 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.

Requirements

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

Responsibilities

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.
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