Machine Learning Engineer

In this onsite Machine Learning Engineer role in Irvine, CA, you will build and operationalize ML models and automated training and inference pipelines to improve business workflows and customer experiences.

• Build, deploy, and optimize ML systems by working with the team on model training, deployment, monitoring, and continuous optimization
• Develop automated ML pipelines for both model training and inference
• Drive ML research to production across ML algorithms, feature engineering, analysis, modeling, and production deployment
• Collaborate across ML engineering to help mature the use of machine learning within the organization
• Learn the business context by building a deep understanding of products, services, data, and customers to support personalized experiences
• Identify ML opportunities to improve business workflows and processes using machine learning technology
• Support additional initiatives by performing other related duties and projects as directed by management

Requirements

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

Technologies

• Python
• SQL
• AWS
• MxNet/Gluon
• Tensorflow
• scikit-learn
• pandas
• pyTorch
• Keras
• xgboost
• LightGBM
• Turi Create
• Nvidia Digits
• AWS RedShift
• Aurora
• S3
• DynamoDB
• MySQL
• PostgreSQL
• EC2
• Lambda
• Step Functions
• SageMaker
• DeepLens
• Rekognition
• IoT
• GreenGrass
• Comprehend
• Lex/Polly
• Transcribe

Pay Range

• $113,000 – $115,000.00 per year

Location: Irvine, CA (onsite)

Education: Master’s degree in Machine Learning, Deep Learning, or a computer science-related field