Full time Manager Data and Analytics Group
This role is remote eligible, which means you would work virtually from home or another non-Best Buy location.
We believe that our company’s success depends on the passion and creativity of our amazing employees. To create environments in which our people can fully thrive, we turn to our guiding behaviors: Be human. Make it real. Think about tomorrow. These set the tone for Best Buy, along with our Rallying Cry: Let’s talk about what’s possible. Our supportive leaders collaborate with their teams through ongoing feedback and two-way dialogue to maintain a culture continual learning. All these factors combine to create an unbeatable experience for both customers and employees. If you like to have fun while you work, build confidence and grow your career, you’ll fit right in.
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.
As aMachine Learning Engineer, 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 software engineering skills and interest in ML and AI to productionize ML models on GCP. You will build reusable tools and components to enable codeless deployments of ML modeling pipelines. Your work will unleash the next generation of customer experiences and transform the way Best Buy operates day-to-day.
Join us if you like to:
- Take a model prototype and productionize it programmatically. Productionization on the cloud involves building data pipelines, training and inference pipelines and pre and post processing routines
- Have strong interest in machine learning and ability to collaborate with data and applied machine learning scientists
- Possess excellent communication skills to be able to communicate with peers and stakeholders
- Enjoy spending your day writing and reviewing code; also participate and lead design discussions
- Are excited by latency tuning of advanced deep learning models and scaling ML solutions to enterprise scale to realize customer impact
- Bachelor's degree in a highly quantitative field (Computer Science, Engineering, Physics, Math, Operations Research or related) or equivalent experience
- 2 years of experience with database languages (SQL, PL/SQL, PG-PL/SQL), version control (Git), data structures and algorithms
- 2 years of experience in writing production quality software in Python; knowledge of Unit testing in Python, Mocking, Pytest.
- 2 years of experience in architecting ML solutions given an abstract business problem
- Understanding of MLOps, Model development lifecycle with knowledge of Training and Deployment pipelines for Machine Learning solutions on the cloud.
- 2 years of experience building training and inference pipelines on GCP and/or AWS
- Master's degree or Ph.D in a highly quantitative field (Computer Science, Engineering, Physics, Math, Operations Research or related)
- Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.) with knowledge of model serialization and deserialization
- Experience with GCP services like Vertex AI and Kubeflow are desirable but not required if they have experience with comparable services like Airflow, Argo etc.
- Experience developing with containers and Kubernetes in cloud computing environments (AWS/GCP)
Auto Req. ID887239BR
Location Number100048 Remote - Washington
Pay Range$86,100.00 - $154,100.00/hr