At Shipt, we are transforming the grocery shopping experience and giving time back to consumers. Shipt shoppers handpick fresh groceries and household essentials, then deliver them to your door in as little as one hour.
The Core Recommendations team at Shipt is looking for a Principal applied scientist to help build the next generation of our e-Commerce recommendations engines. Our team develops customer facing machine learning models that enable product discovery across a gigantic multi-retailer item catalog. Our ideal candidate will be able to develop and apply core algorithms that strengthen Shipt’s marketplace and advance the industry state of the art.
We’re seeking an experienced machine learning scientist that has built real time personalized recommender systems before and can lead the overall algorithm strategy in this space for the company.
This role can be located 100% remote, or in one of our offices located in San Francisco or Birmingham.
Lead overall technical machine learning strategy and development for Shipt’s core e-Commerce product search engine
Mentor junior and senior level scientists
Work through all phases of development including problem formulation, data understanding, model prototyping, evaluation, deployment and maintenance
Collaborate with other members of the Data Science and Data Engineering teams on ways to approach problems, audit code, and share new techniques
Work closely with functional team leaders to explain your findings and support reproducibility
Develop systems and techniques for model evaluation in both offline and online settings
Stay up to date on developments in industry and academia and contribute to its advancement
Master’s or PhD in Computer Science, Statistics, or other related field in machine learning and/or information retrieval
7+ years of industry or research experience in Machine Learning with a focus on recommendation engines
Published machine learning research in KDD, WWW, RecSys, SIGIR, or a similar conference
Expertise in PyTorch, Tensorflow, or similar deep learning frameworks
Hands-on industry experience building real time personalized ranking models, multi-armed bandits, and/or deep reinforcement learning
Comfortable with a database query language (SQL, BigQuery, etc.)
Comfortable writing and debugging production code
Ability to communicate results with non-technical stakeholders
Prior industry experience with product recommendation engines for E-commerce
Experience deploying machine learning models to production
Familiarity with on-demand and/or multi-sided marketplaces
Experience with distributed deep learning (multiple GPUs)
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.