Applied Machine Learning Engineer

Best Buy is a company dedicated to enriching lives through technology. They are seeking an Applied Machine Learning Engineer to build and operate ML systems for product discovery and personalization, collaborating with data scientists and engineers to ensure reliable and scalable solutions.

Responsibilities:

• Build and maintain ML training pipelines and infrastructure (Vertex AI Pipelines, BigQuery, GCS) that enable data scientists to train and evaluate models
• Productionize ML models as real-time, low-latency services using Cloud Run, Vertex AI, and containerized microservices
• Set up and own monitoring, logging, and alerting for production ML services
• Develop feature engineering, embedding, and data pipelines using GCP data services
• Partner with Data Scientists and ML Researchers to take models from research to production and iterate based on real-world performance

Requirements:

• Bachelor's degree in Computer Science, Engineering, Math, or related field (or equivalent experience)
• 3 years of experience in ML/AI, data engineering, or software development
• 3 years of experience building, deploying, and serving real-time ML/AI models with ultra-low latency and high throughput, as resilient, scalable, cloud native services
• 2 years of experience building data engineering pipelines, ML/AI driven products or other related functions (e.g. software engineering, data science)
• 2 years of Python and SQL skills
• 2 years of experience in software design, test-driven development, and implementation using a general-purpose programming language (e.g., Python, Scala, Rust, C++, etc.)
• Solid understanding of supervised/unsupervised learning, deep learning, and Gen AI
• Experience with GCP: Vertex AI, Cloud Run, Cloud Functions, BigQuery, or GCS
• Hands-on with ML model serving (FastAPI, Vertex AI endpoints, or similar) and Docker/Kubernetes
• Familiarity with embeddings, vector search, or information retrieval systems
• Experience with monitoring and observability for production ML systems
• Exposure to PyTorch, Hugging Face Transformers, or LLMs/generative AI in production