Machine Learning Engineering Intern (Hybrid) - June 2024

Key Skills

Aartificial intelligence, Deep Learning, Forecasting, Machine Intelligence, Machine learning techniques, Natural Language Processing (NLP), Operations, Optimization, Supply Chain Management

Job Description

We’re searching for you: fresh talent with new ideas, innovation, passion, and drive to bring to Staples. We have student and graduate opportunities where you’ll help the Staples, Inc. organization be more successful and productive while building a purposeful career. Whether you are looking for a summer internship, co-op, or an entry-level role, we’ll help you develop the technical and soft skills you need to thrive in the future.

This intern position is a part of a hybrid work model, 3 days in the office and 2 days remote.

What you bring to the table:

• Collaborative – able to build partnerships and work collaboratively with others to meet shared objectives
• Customer Focused – able to identify and understand internal or external customer needs and interests and deliver customer-centric solutions
• Inclusive – dedicated to fostering an inclusive environment consisting of diverse individuals from varying backgrounds and cultures
• Innovative – develop new insights; question conventional approaches; encourage new ideas; design and implement new solutions
• Self-Developer – actively seeks new ways to grow and be challenged using both formal and informal development channels

Host organization presentation:

The ML Engineering team at Staples is building intelligent systems to support various business use cases (ranging from order fulfillment, last-mile delivery, supply chain optimization, forecasting, search, recommendation, content management, customer segmentation, and personalization). We design, prototype, and implement end-to-end Machine Learning systems leveraging in-house data. Our focus areas include Machine Learning, Operations Research, Deep Learning, Reinforcement Learning, Natural Language Processing, Leveraging Generative AI, Demand Forecasting, Personalization, ML Inference at Scale, and all other aspects of Machine Intelligence in the e-commerce landscape.

The primary focus of the project is to build an intelligence platform to power Staples machine learning applications. The project will involve building reusable modules and pipelines (to perform feature engineering, model training, tuning, validation, and inferencing). The modeling scope will span across multiple business problems (such as dynamic pricing, customer insights, product search and recommendation, question answering, content enrichment, and campaign asset generation). Staples has a rich data set from multiple business functions/systems. We will be leveraging in-house data to train a suite of ML models hosted on the intelligence platform.

Project focus areas:

The primary objective here is to build a general-purpose intelligence platform on Azure leveraging Azure ML, Azure Open AI, and other Azure resources. This will enable Staples in the rapid development of machine learning models. For example, a language processing pipeline built to support item matching can be leveraged to support product search and recommendation. The focus will be on creating the necessary infrastructure, building reusable modules/models/pipelines, and how to scale the inference pipeline in a cost/compute eRective manner. For instance, the item matching system used by Staples merchants will have 500 inference requests per day compared to several hundred thousand inference requests every day to power Staples.com product search engine.

Impact:

This project will focus on the foundational intelligence platform powering multiple customer-facing machine learning use cases within Staples.

Evaluation:

The success of this project will be measured in multiple dimensions such as 1.) How (cost/compute/reusable/scale) eRective is the intelligence platform? 2.) How easy it is to onboard new models and light up new use cases?

What’s needed- Basic Qualifications:

• Actively pursuing a master’s degree
• Prior knowledge of machine learning, deep learning, language processing, optimization
• Strong Azure programming skills and a relevant mathematical background will be a plus

Preferred Qualifications:

• Enjoy working in teams and being highly communicative
• Able to multi-task and be flexible to new initiatives