ML 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.

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.

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

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.

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.