Machine Learning Engineer

Glidewell Dental is hiring a Machine Learning Engineer to help build and improve machine learning systems that support real business workflows. This onsite role in Irvine, CA focuses on taking ML from research to production, with a strong emphasis on automated training and inference pipelines, ongoing monitoring, and continuous optimization. The salary range for this position is $113,000 to $115,000 per year.

What you’ll do

• Collaborate with the team to build, deploy, monitor, and continuously optimize ML models.
• Develop automated ML training and inference pipelines and support reliable production workflows.
• Build a deeper understanding of products, services, data, and customers to enable personalized experiences.
• Research and apply machine learning engineering topics such as ML algorithms, feature engineering, analysis, modeling, and production deployment.
• Work with Machine Learning Engineers to mature the use of machine learning across the organization.
• Identify new opportunities to apply ML technology to improve business processes and workflows.
• Handle other related duties and projects as directed by management based on business needs.

What you bring

• Master’s degree in Machine Learning, Deep Learning, or a computer science-related field.
• PhD preferred.
• Previous relevant working experience required.
• Strong understanding of fundamental concepts, practices, and procedures in the ML field.
• Experience with data discovery, data aggregation, and feature engineering, with excellent SQL query writing skills preferred.
• Experience preferred in training, evaluating, optimizing, deploying, and maintaining ML models on production systems.
• Experience preferred with logging, tracking, A/B testing, and evaluating performance of different ML algorithms and models in production.
• Strong Python development skills and experience building data-driven, scalable, and reliable applications, with AWS preferred.
• Experience applying ML algorithms to optimization problems, including customer sales prediction, recommendation engines, sentiment analysis, deep learning for image and natural language, customer segmentation/clustering, and object detection preferred.
• Experience preferred with popular open source ML/Deep learning libraries such as MxNet/Gluon, TensorFlow, scikit-learn, pandas, PyTorch, Keras, xgboost, LightGBM, Turi Create, and Nvidia Digits.
• Experience preferred with relational and non-relational, high-scale processing and storage frameworks including SQL, AWS RedShift, Aurora, S3, DynamoDB, MySQL, and PostgreSQL.
• Experience preferred with AWS Serverless architecture and AWS native services such as EC2, Lambda, Step Functions, SageMaker, DeepLens, Rekognition, IoT, GreenGrass, Comprehend, Lex/Polly, and Transcribe.

Core tools you’ll work with

Python, SQL, AWS, plus ML and data technologies including MxNet/Gluon, TensorFlow, scikit-learn, pandas, PyTorch, Keras, xgboost, LightGBM, Turi Create, Nvidia Digits, and data/storage services such as AWS RedShift, Aurora, S3, DynamoDB, MySQL, PostgreSQL. AWS services may include EC2, Lambda, Step Functions, SageMaker, DeepLens, Rekognition, IoT, GreenGrass, Comprehend, Lex/Polly, and Transcribe.