Hiring: Senior ML Engineer Company: Weyerhaeuser Location: Seattle, WA Job Posted Time: 2026-09-10 10:38:13 Employment Type: Full-time Target Skills & Keywords : AWS, Airflow, Ansible, Azure, CI/CD, Docker, Git, Kubeflow, Kubernetes, MLflow, Machine Learning, Microservices, Python, SAP, SQL, SageMaker, Snowflake, Systems Design, Terraform About the job Experience: •6-8 years of experience building and supporting production machine learning systems, data platforms, or cloud-native software services in enterprise environments. •ML & Model Development •Applied hands-on capability in end-to-end machine learning lifecycle, including feature engineering, model development, training, evaluation, and operationalizing models in production envoirnments. •Operational familiarity with tools such as MLflow, SageMaker, Kubeflow, Statsig, Airflow, or similar orchestration and experiment-tracking frameworks. Required Skills: •Develop Machine Learning Models •Design, build, and optimize machine learning models, including feature engineering, model selection, training, and validation across multiple AI use cases. •Operationalize and deploy batch and real-time inference solutions using cloud-native services and containerized architectures, ensuring performance, reliability, and cost efficiency. •ML System Design & Integration •Design end-to-end ML systems that integrate seamlessly with application use cases and data platforms, supporting scalable and maintainable solutions. •Implement robust monitoring for model performance, data drift, prediction accuracy, latency, and implement retraining strategies based on feedback and evolving data. Establish alerting and diagnostics to support rapid issue detection and remediation. •Develop and maintain CI/CD workflows for machine learning assets, including code, features, models, and configurations, enabling safe and repeatable releases into production. •Partner cross-functionally with data engineering teams to ensure reliable data ingestion, feature engineering, and versioning to support consistent model behavior across environments. Design, and build pipelines that enable efficient training and inference ML workflows. Qualifications: •Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field; advanced degree is a plus. Compensation: •$106,900 - $160,400 / year •Also be eligible for our Annual Incentive Program, which offers a cash bonus targeting 15% of base pay Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!