ML Engineer

Machine Learning Engineer

At Weyerhaeuser, we sustainably manage forests and manufacture products that make the world a better place. With a commitment to excellence and innovation, we leverage technology to enhance operational efficiency across timberlands, wood products, and corporate functions. As we continue to scale AI across the enterprise, we are seeking a skilled ML Engineer to design, build, and operationalize machine learning solutions that are reliable, scalable, secure, and delivering measurable business value in production.

About the Role

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 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.

Requirements

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 environments.

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.

About Weyerhaeuser

We sustainably manage forests and manufacture products that make the world a better place. We're serious about safety, driven to achieve excellence, and proud of what we do. With multiple business lines in locations across North America, we offer a range of exciting career opportunities for smart, talented people who are passionate about making a difference. We know you have a choice in your career. We want you to choose us.

What We Offer

Compensation

• Salary range: $106,900–$160,400 based on level of skills, qualifications, and experience.
• Eligible for our annual merit-increase program.
• 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

• Comprehensive employee benefits plan covering medical, dental, vision, short and long-term disability, and life insurance.
• Pre-tax Health Savings Account option with company contribution.
• Voluntary Long-Term Care and Employee Assistance Programs.
• Support for personal volunteerism, diversity networks, mentoring, and training and development opportunities.

Retirement

• 401k plan with paid company match in addition to a contribution equal to 5% of eligible pay.

Paid Time Off or Vacation

• 3 weeks of paid vacation during the first year of employment for eligible employees scheduled to work 25 hours or more per week.
• Vacation accrual beginning after six months of employment.
• Eleven paid holidays per year (88 holiday hours total).
• Paid parental leave for all full-time employees.

Equal Opportunity

Weyerhaeuser is an equal opportunity employer. Inclusion is one of our five core values and we strive to maintain a culture where all our people feel a sense of belonging, opportunity and shared purpose. We are committed to recruiting a diverse workforce and supporting an equitable and inclusive environment that inspires people of all backgrounds to join, stay and thrive with our team.