MLOps Engineer

Weyerhaeuser • Seattle, WA

14h

About The Position

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 MLOps Engineer to operationalize machine learning solutions and ensure they are reliable, scalable, secure, and delivering measurable business value in production.
The MLOps Engineer will be responsible for building, deploying, monitoring, and operating 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 implement standardized MLOps patterns that support repeatability, governance, and continuous improvement across the AI lifecycle. The ideal candidate has hands-on experience with ML deployment pipelines, cloud-native infrastructure, model monitoring, and enterprise data platforms—and is motivated by building systems that scale responsibly.

Requirements

• 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.
• Hands-on experience with model lifecycle management, including training pipelines, model registries, deployment strategies, and monitoring.
• Experience with cloud platforms such as AWS or Azure, including containerization (Docker), orchestration (Kubernetes or managed equivalents), and infrastructure-as-code (Terraform\Ansible).
• Familiarity with tools such as MLflow, SageMaker, Kubeflow, Statsig, Airflow, or similar orchestration and experiment-tracking frameworks.
• Strong proficiency in Python and git; working knowledge of SQL; familiarity with APIs and microservices architectures.
• Strong understanding of reliability, scalability, security, and cost management in production systems.
• Ability to work effectively with both technical and non-technical stakeholders, translating operational requirements into practical solutions.
• Demonstrated curiosity and commitment to staying current with evolving MLOps practices, tools, and AI platform capabilities.

Nice To Haves

• 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 and computer vision projects.

Responsibilities

• Operationalize Machine Learning Models
• Design, build, and maintain end-to-end MLOps pipelines that support model training, validation, deployment, and automatic retraining across multiple AI use cases.
• Model Deployment & Serving
• Deploy batch and real-time inference workloads using cloud-native services and containerized architectures, ensuring performance, reliability, and cost efficiency.
• Monitoring & Observability
• Implement robust monitoring for model performance, data drift, prediction quality, latency, and system health. 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.
• Data & Feature Pipelines
• Collaborate with data engineering teams to ensure reliable data ingestion, feature generation, and versioning to support consistent model behavior across environments. Design, build and support online and offline feature stores.
• 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 architect and implement modeling work into production-ready services.
• Platform Enablement
• Contribute to shared MLOps tooling, standards, and reference architectures that accelerate AI delivery across Weyerhaeuser’s AI Factory.
• Continuous Improvement
• Identify opportunities to improve reliability, automation, scalability, and developer experience across the AI delivery lifecycle.

Benefits

• 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%25 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%25 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level