We at Best Buy work hard every day to enrich the lives of customers through technology, whether they come to us online, visit our stores or invite us into their homes. We do this by solving technology problems and addressing key human needs across a range of areas, including entertainment, productivity, communicating with coworkers and loved ones, preparing nutritious food, providing security for your home and family, and helping you take your health to the next level.
This role is intended to be hybrid, which means you must be located within a drivable distance to Boston, Seattle, or Minneapolis Corporate locations.
As a Machine Learning Scientist/Engineer Intern, you’ll have the opportunity to work alongside industry experts researching, developing, and applying cutting-edge machine learning and artificial intelligence algorithms to build innovative technologies, services, and products that solve the company's hardest problems and accelerate Best Buy's core growth. In this role you will combine your passion for software engineering and ML/AI algorithms to contribute to a team developing and operationalizing ML models and production quality code to unleash next generation of customer experiences and transform the way Best Buy operates day-to-day.
Join us if you like to:
- Developing Machine Learning solutions and services leveraging state-of-the-art techniques
- Applying software engineering skills to develop and deploy solutions that can scale to millions of requests per second with millisecond latency
- Utilizing broad and deep knowledge of machine learning and software engineering to contribute to the roadmap of Best Buy’s core machine learning capabilities
- Building real products that influence and enhance the lives of millions of people and drive and deliver tens of millions of dollars in impact to Best Buy’s bottom line
- Having fun!
- Pursuing a master’s or PHD degree graduating between Fall 2023 and Spring 2024
- Must be able to work out of one of the following HUB locations; Seattle, Boston, or Minneapolis.
- Foundational machine learning and algorithmic background with some understanding of at least one of the following areas: supervised and unsupervised learning methods, reinforcement learning, deep learning, Bayesian inference, graphical modeling, or nonlinear/stochastic optimization
- Experience with at least one data science/analytics programming language (e.g. Python, R, Julia)
- Foundational software engineering skills and programming experience with one of more programming languages - Python, R, Julia, Scala or Java
- Experience using high performance machine learning libraries and/or deep learning frameworks like PyTorch or Tensorflow
- Fluency with Python and SQL
- Experience working over cloud
- Knowledge of functional programming