The ML Engineer will be responsible for developing, training, deploying, and operationalizing machine learning systems across Weyerhaeuser's AI portfolio, including pricing optimization, industrial AI, geospatial analytics, and generative AI solutions. This role sits at the intersection of data science, software engineering, and cloud infrastructure, enabling the transition from experimental models to trusted, production-grade AI services.

You will work closely with data scientists, AI engineers, product managers, and platform teams to build scalable ML systems that support repeatability, governance, and continuous improvement across the AI lifecycle. The ideal candidate has hands-on experience with model development, feature engineering, and operationalizing models in the production environments, along with strong software engineering fundamentals. You are motivated by solving complex business problems and building intelligent systems that scale responsibly.

Primary Responsibilities

Develop Machine Learning Models
Design, build, and optimize machine learning models, including feature engineering, model selection, training, and validation across multiple AI use cases.

Model Deployment & Serving
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.
Monitoring & Observability
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.

CI/CD for AI Systems
Develop and maintain CI/CD workflows for machine learning assets, including code, features, models, and configurations, enabling safe and repeatable releases into production.

Data & Feature Pipelines
Collaborate 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.

Governance & Responsible AI
Support enterprise AI governance by enabling model lineage, reproducibility, auditability, and controlled promotion across environments in alignment with Responsible AI principles.

Cross-Functional Collaboration
Partner with data scientists, AI engineers, product managers, IT, and cybersecurity teams to operationalize models into production-ready solutions.

Platform Enablement
Contribute to shared ML tooling, standards, and reference architectures that accelerate delivery of machine learning solutions across Weyerhaeuser's AI Factory.

Continuous Improvement
Identify opportunities to improve reliability, automation, scalability, and developer productivity across the AI delivery lifecycle.

Qualifications
Education
Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field; advanced degree is a plus.

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
Hands-on experience with end-to-end machine learning lifecycle, including feature engineering, model development, training, evaluation, and operationalizing models in production envoirnments.

Cloud & Infrastructure
Experience with cloud platforms such as AWS or Azure, including containerization (Docker), orchestration (Kubernetes or managed equivalents), and infrastructure-as-code (Terraform\Ansible).

Data & ML Tooling
Familiarity with tools such as MLflow, SageMaker, Kubeflow, Statsig, Airflow, or similar orchestration and experiment-tracking frameworks.

Programming Skills
Strong proficiency in Python and version control (git); working knowledge of SQL; familiarity with APIs and microservices architectures.

Enterprise Data Platforms
Experience integrating ML workloads with enterprise data platforms such as Snowflake and transactional systems such as SAP is highly desirable. Familiarity with geospatial data sets.

Operational Mindset
Strong understanding of reliability, scalability, security, and cost optimization when operationalizing models in production.

Collaboration & Communication
Ability to work effectively with both technical and non-technical stakeholders, translating business requirements into practical solutions.

Learning Orientation
Demonstrated curiosity and commitment to staying current with evolving ML practices, tools, and AI platform capabilities.

What We Offer:

Compensation: This role is eligible for our annual merit-increase program, and we are targeting a salary range of $106,900-$160,400 based on your level of skills, qualifications and experience. You will also be eligible for our Annual Incentive Program, which offers a cash bonus targeting 15% of base pay. Potential plan funding may range from zero to two times that target.

Benefits: When you join our team, you and your dependents will be offered coverage under our comprehensive employee benefits plan, which includes medical, dental, vision, short and long-term disability, and life insurance. We offer a pre-tax Health Savings Account option which includes a company contribution. Other benefit options are also available such as voluntary Long-Term Care and Employee Assistance Programs. We also support personal volunteerism, sponsor a host of diversity networks, promote mentoring, and provide training and development opportunities to help you chart your path to a fulfilling career.

Retirement: Employees are able to enroll in our company's 401k plan, which includes a paid company match in addition to our contribution equal to 5% of your eligible pay

Paid Time Off or Vacation: We provide eligible employees who are scheduled to work 25 hours or more per week with 3-weeks of paid vacation to use during your first year of employment. In addition, after being employed for six months, eligible employees begin to accrue vacation for future use. We also recognize eleven paid holidays per year, providing a total of 88 holiday hours and paid parental leave for all full-time employees.

Attention Internal Applicants: To ensure transparency across the organization, please have a discussion with your manager prior to applying for any new opportunities. If you need any help facilitating this conversation, please reach out to your HR Representative for guidance. For more information on how to apply, including best practices for updating your profile or partnering with HR and Recruiting, please visit our internal applicant page on Roots: wy.com/applicants