Mlops Engineer Jobs in USA with Visa Sponsorship
MLOps Engineer roles are among the most actively sponsored positions in the U.S. tech industry, with employers regularly filing H-1B petitions for qualified candidates. Most openings require a degree in computer science, data science, or a related engineering field to meet specialty occupation standards. For detailed occupation requirements, see the O*NET profile.
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INTRODUCTION
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.
ROLE AND RESPONSIBILITIES
Primary 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.
BASIC 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.
MLOps & ML Systems:
Hands-on experience with model lifecycle management, including training pipelines, model registries, deployment strategies, and monitoring.
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 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 and computer vision projects.
Operational Mindset:
Strong understanding of reliability, scalability, security, and cost management in production systems.
Collaboration & Communication:
Ability to work effectively with both technical and non-technical stakeholders, translating operational requirements into practical solutions.
Learning Orientation:
Demonstrated curiosity and commitment to staying current with evolving MLOps practices, tools, and AI platform capabilities.
LOCATION
Primary Location
USA-WA-Seattle
SCHEDULE
Full-time
JOB TYPE
Experienced
SHIFT
Day (1st)
COMPENSATION
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
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.

INTRODUCTION
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.
ROLE AND RESPONSIBILITIES
Primary 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.
BASIC 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.
MLOps & ML Systems:
Hands-on experience with model lifecycle management, including training pipelines, model registries, deployment strategies, and monitoring.
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 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 and computer vision projects.
Operational Mindset:
Strong understanding of reliability, scalability, security, and cost management in production systems.
Collaboration & Communication:
Ability to work effectively with both technical and non-technical stakeholders, translating operational requirements into practical solutions.
Learning Orientation:
Demonstrated curiosity and commitment to staying current with evolving MLOps practices, tools, and AI platform capabilities.
LOCATION
Primary Location
USA-WA-Seattle
SCHEDULE
Full-time
JOB TYPE
Experienced
SHIFT
Day (1st)
COMPENSATION
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
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.
How to Get Visa Sponsorship as a Mlops Engineer
Target companies with a proven H-1B filing history
Large tech employers and AI-focused startups file H-1B petitions for MLOps roles at high rates. Focusing your search on companies with consistent sponsorship records significantly improves your odds of receiving a petition before the lottery.
Make sure your degree field aligns with the role
USCIS treats MLOps as a specialty occupation requiring a degree in computer science, data engineering, or a related technical field. A business or unrelated degree, even with strong experience, can complicate your petition and invite a Request for Evidence.
Get proficient with the full MLOps toolchain
Employers filing H-1B petitions for MLOps Engineers typically list specific tools like Kubernetes, MLflow, Kubeflow, and CI/CD pipelines in LCAs. Demonstrating hands-on experience with these tools strengthens both your candidacy and the specialty occupation argument.
Understand cap-exempt employer opportunities
Universities, nonprofit research institutions, and affiliated organizations are exempt from the H-1B lottery cap. MLOps roles at these employers can be filed any time of year, giving candidates who miss the lottery a practical alternative path to status.
Consider the O-1A visa if you have recognized research contributions
MLOps Engineers with published papers, conference presentations, open-source project recognition, or roles at cutting-edge AI labs may qualify for the O-1A. It has no annual cap and no lottery, making it a strong fallback for high-achieving candidates.
Browse Migrate Mate for roles filtered by sponsorship availability
Not every job listing makes sponsorship eligibility clear upfront. Migrate Mate surfaces MLOps Engineer openings from employers actively willing to sponsor, saving you from applying to roles where sponsorship was never on the table.
Mlops Engineer jobs are hiring across the US. Find yours.
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Get Access To All JobsFrequently Asked Questions
Does MLOps Engineer qualify as a specialty occupation for H-1B purposes?
Yes, MLOps Engineer consistently qualifies as a specialty occupation under USCIS standards. The role requires theoretical and practical application of computer science, machine learning systems design, and software engineering, all of which demand at minimum a bachelor's degree in a directly related field. Approval rates for software and ML engineering roles remain among the highest across H-1B petitions.
What degree do I need for an employer to sponsor my H-1B as an MLOps Engineer?
A bachelor's degree or higher in computer science, data science, machine learning, electrical engineering, or a closely related technical discipline is the standard requirement. Degrees in unrelated fields, even combined with relevant experience, can weaken the specialty occupation argument. If your degree is in a tangential area, an attorney can assess whether your coursework and experience still support the petition.
How competitive is H-1B sponsorship for MLOps Engineers compared to other tech roles?
MLOps is a high-demand specialization, and employers filing for these roles tend to be well-resourced companies familiar with the sponsorship process. That said, all cap-subject H-1B petitions still go through the same lottery. In recent fiscal years, selection rates have hovered around 20 to 30 percent, so candidates benefit from targeting multiple employers and exploring cap-exempt alternatives simultaneously.
Can I get sponsored as an MLOps Engineer if I'm currently on OPT or STEM OPT?
Yes, and this is one of the most common paths. If you're on F-1 OPT, your employer files an H-1B petition in March for an October 1 start. STEM OPT extensions give computer science and engineering graduates up to three additional years of work authorization, providing a meaningful runway to secure sponsorship even if you miss the first lottery cycle.
Where can I find MLOps Engineer jobs where employers are open to sponsorship?
Migrate Mate is built specifically for international candidates seeking sponsored roles. You can browse MLOps Engineer openings filtered by employers willing to sponsor work visas, which removes the friction of discovering mid-process that a company won't file a petition. This is especially useful for candidates who need to move quickly due to OPT or grace period deadlines.
What is the prevailing wage requirement for sponsored Mlops Engineer jobs?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.
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