Senior Mlops Engineer Jobs in USA with Visa Sponsorship
Senior MLOps Engineers are strong candidates for H-1B visa and O-1 visa sponsorship. The role qualifies as a specialty occupation requiring a bachelor's degree or higher in computer science, engineering, or a related field, and employers routinely sponsor across both cap-subject and cap-exempt pathways. For detailed occupation requirements, see the O*NET profile.
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Get Access To All JobsThe work we do has an impact on millions of lives, and you can be a part of it. We help protect our customers against life’s uncertainties. Regardless of where you work within the company, you’ll be helping provide protection and peace of mind when our customers need it most.
Protective Life is transforming how it builds and operates software — moving to a product operating model organized around empowered, outcome-oriented teams — and is scaling its data and AI capabilities to serve customers and run the business better. Voyager is one of these product pods, spanning our Life, Annuities, and Employee Benefits lines.
The DataOps/MLOps Lead owns the platform and operating model that lets data and ML engineers ship reliably. You build the paved paths — CI/CD, orchestration, observability, environments, and governance automation — on our Databricks Lakehouse on Microsoft Azure, so that pipelines and models move from development to governed production quickly, safely, and repeatably.
This is a hands-on technical leadership role: you set standards, automate the operational backbone, mentor engineers, and are accountable for the reliability, security, cost, and auditability of the pod's data and ML systems in a regulated insurance environment.
KEY RESPONSIBILITIES
- Own the DataOps/MLOps platform and operating model — the paved paths, automation, and tooling that data and ML engineers use to build and run pipelines and models reliably.
- Lead CI/CD standards and pipelines in Azure DevOps (ADO) for data pipelines and ML models — build, test, and release automation, environment promotion, and repeatable, auditable deployments.
- Standardize orchestration on Dagster — reusable assets, scheduling, backfills, dependency management, and run observability across the pod's pipelines.
- Operationalize the ingestion and transformation stack — dlt (dltHub) and dbt — with automated testing, CI checks, and safe deployment of changes.
- Build MLOps foundations with the ML engineering team — MLflow model registry, Databricks Model Serving, automated deployment, monitoring, drift detection, and retraining triggers.
- Establish data and model observability — freshness, quality, lineage, latency, drift, and cost — with alerting and clear SLAs/SLOs.
- Administer and govern the Databricks Lakehouse on Azure — workspace configuration, Unity Catalog governance, access controls, and policy automation.
- Manage infrastructure as code and environments — reproducible dev/test/prod setups (e.g., Terraform), secrets management, and least-privilege access.
- Own reliability and incident practices — on-call, runbooks, root-cause analysis, and continuous improvement for data and ML services.
- Drive cost visibility and optimization (FinOps) across compute, storage, and model serving.
- Automate governance and compliance controls — audit logging, model and pipeline inventories, approval workflows, and evidence collection for a regulated environment.
- Provide technical leadership and mentoring — coach engineers on operational excellence and set the platform standards the pod builds on.
QUALIFICATIONS
REQUIRED QUALIFICATIONS
- 8+ years in data, ML, or platform engineering, or in SRE/DevOps, including several years operating production data and/or ML systems.
- Demonstrated technical leadership — setting standards, building paved paths and automation, and mentoring engineers (formal people management not required, but valued).
- Strong CI/CD expertise with Azure DevOps (ADO) — build/release pipelines, environment promotion, automated testing — and Git-based workflows.
- Hands-on experience with orchestration (Dagster or equivalent) and the modern data stack — dlt (dltHub) ingestion and dbt modeling — on a Databricks lakehouse (Delta Lake).
- MLOps experience — MLflow model registry, model deployment/serving, monitoring, drift detection, and retraining automation.
- Infrastructure-as-code and cloud platform administration on Microsoft Azure (compute, storage, identity, networking basics); Terraform or equivalent.
- Strong Python and SQL for automation and tooling.
- Experience with observability/monitoring tooling and SRE practices — SLAs/SLOs, alerting, and incident management.
- Demonstrated rigor in security, access control, and secure, compliant handling of sensitive data.
- Bachelor's degree in Computer Science, Engineering, or a related field — or equivalent practical experience.
PREFERRED QUALIFICATIONS
- Experience in financial services or insurance platform work, and familiarity with model risk and regulatory audit expectations.
- Databricks administration — Unity Catalog, cluster policies, and Mosaic AI — and familiarity with Azure Machine Learning.
- Containerization and orchestration (Docker, Kubernetes; Azure AKS or Container Apps).
- Experience with data-quality / observability tooling (e.g., Great Expectations, Monte Carlo, or similar).
- Experience automating responsible-AI and model-governance controls.
- Relevant certification such as Databricks Certified Data Engineer/ML Engineer, Microsoft Azure DevOps Engineer, or Azure Administrator.
Protective’s targeted salary range for this position is $124,500 to $170,000. Actual salaries may vary depending on factors, including but not limited to job location, skills, and experience. The range listed is just one component of Protective’s total compensation package for employees.
This position also offers additional incentive opportunities through an annual incentive based on individual and Company performance.
Employee Benefits: We aim to protect the wellbeing of our employees and their families with a broad benefits offering. In addition to offering comprehensive health, dental and vision insurance, we support emotional wellbeing through mental health benefits and an employee assistance program. Work/life balance is important and Protective offers a variety of paid time away benefits (e.g., paid time off, paid parental leave, short-term disability, and a cultural observance day). The financial health of our employees is just as important as physical and emotional health. Some of the financial wellbeing benefits include contributions to healthcare accounts, a pension plan, and a 401(k) plan with Company matching. All employees are encouraged to protect their overall wellbeing by engaging in ProHealth Rewards, Protective’s platform to improve wellbeing while earning cash rewards.
Eligibility for certain benefits may vary by position in accordance with the terms of the Company’s benefit plans.
Accommodations for Applicants with a Disability: If you require an accommodation to complete the application and recruitment process due to a disability, please email eric.hess@protective.com. This information will be held in confidence and used only to determine an appropriate accommodation for the application and recruitment process.
Please note that the above email is solely for individuals with disabilities requesting an accommodation. General employment questions should not be sent through this process.
We are proud to be an equal opportunity employer committed to being inclusive and attracting, retaining, and growing an inclusive workforce.
The work we do has an impact on millions of lives, and you can be a part of it. We help protect our customers against life’s uncertainties. Regardless of where you work within the company, you’ll be helping provide protection and peace of mind when our customers need it most.
Protective Life is transforming how it builds and operates software — moving to a product operating model organized around empowered, outcome-oriented teams — and is scaling its data and AI capabilities to serve customers and run the business better. Voyager is one of these product pods, spanning our Life, Annuities, and Employee Benefits lines.
The DataOps/MLOps Lead owns the platform and operating model that lets data and ML engineers ship reliably. You build the paved paths — CI/CD, orchestration, observability, environments, and governance automation — on our Databricks Lakehouse on Microsoft Azure, so that pipelines and models move from development to governed production quickly, safely, and repeatably.
This is a hands-on technical leadership role: you set standards, automate the operational backbone, mentor engineers, and are accountable for the reliability, security, cost, and auditability of the pod's data and ML systems in a regulated insurance environment.
KEY RESPONSIBILITIES
- Own the DataOps/MLOps platform and operating model — the paved paths, automation, and tooling that data and ML engineers use to build and run pipelines and models reliably.
- Lead CI/CD standards and pipelines in Azure DevOps (ADO) for data pipelines and ML models — build, test, and release automation, environment promotion, and repeatable, auditable deployments.
- Standardize orchestration on Dagster — reusable assets, scheduling, backfills, dependency management, and run observability across the pod's pipelines.
- Operationalize the ingestion and transformation stack — dlt (dltHub) and dbt — with automated testing, CI checks, and safe deployment of changes.
- Build MLOps foundations with the ML engineering team — MLflow model registry, Databricks Model Serving, automated deployment, monitoring, drift detection, and retraining triggers.
- Establish data and model observability — freshness, quality, lineage, latency, drift, and cost — with alerting and clear SLAs/SLOs.
- Administer and govern the Databricks Lakehouse on Azure — workspace configuration, Unity Catalog governance, access controls, and policy automation.
- Manage infrastructure as code and environments — reproducible dev/test/prod setups (e.g., Terraform), secrets management, and least-privilege access.
- Own reliability and incident practices — on-call, runbooks, root-cause analysis, and continuous improvement for data and ML services.
- Drive cost visibility and optimization (FinOps) across compute, storage, and model serving.
- Automate governance and compliance controls — audit logging, model and pipeline inventories, approval workflows, and evidence collection for a regulated environment.
- Provide technical leadership and mentoring — coach engineers on operational excellence and set the platform standards the pod builds on.
QUALIFICATIONS
REQUIRED QUALIFICATIONS
- 8+ years in data, ML, or platform engineering, or in SRE/DevOps, including several years operating production data and/or ML systems.
- Demonstrated technical leadership — setting standards, building paved paths and automation, and mentoring engineers (formal people management not required, but valued).
- Strong CI/CD expertise with Azure DevOps (ADO) — build/release pipelines, environment promotion, automated testing — and Git-based workflows.
- Hands-on experience with orchestration (Dagster or equivalent) and the modern data stack — dlt (dltHub) ingestion and dbt modeling — on a Databricks lakehouse (Delta Lake).
- MLOps experience — MLflow model registry, model deployment/serving, monitoring, drift detection, and retraining automation.
- Infrastructure-as-code and cloud platform administration on Microsoft Azure (compute, storage, identity, networking basics); Terraform or equivalent.
- Strong Python and SQL for automation and tooling.
- Experience with observability/monitoring tooling and SRE practices — SLAs/SLOs, alerting, and incident management.
- Demonstrated rigor in security, access control, and secure, compliant handling of sensitive data.
- Bachelor's degree in Computer Science, Engineering, or a related field — or equivalent practical experience.
PREFERRED QUALIFICATIONS
- Experience in financial services or insurance platform work, and familiarity with model risk and regulatory audit expectations.
- Databricks administration — Unity Catalog, cluster policies, and Mosaic AI — and familiarity with Azure Machine Learning.
- Containerization and orchestration (Docker, Kubernetes; Azure AKS or Container Apps).
- Experience with data-quality / observability tooling (e.g., Great Expectations, Monte Carlo, or similar).
- Experience automating responsible-AI and model-governance controls.
- Relevant certification such as Databricks Certified Data Engineer/ML Engineer, Microsoft Azure DevOps Engineer, or Azure Administrator.
Protective’s targeted salary range for this position is $124,500 to $170,000. Actual salaries may vary depending on factors, including but not limited to job location, skills, and experience. The range listed is just one component of Protective’s total compensation package for employees.
This position also offers additional incentive opportunities through an annual incentive based on individual and Company performance.
Employee Benefits: We aim to protect the wellbeing of our employees and their families with a broad benefits offering. In addition to offering comprehensive health, dental and vision insurance, we support emotional wellbeing through mental health benefits and an employee assistance program. Work/life balance is important and Protective offers a variety of paid time away benefits (e.g., paid time off, paid parental leave, short-term disability, and a cultural observance day). The financial health of our employees is just as important as physical and emotional health. Some of the financial wellbeing benefits include contributions to healthcare accounts, a pension plan, and a 401(k) plan with Company matching. All employees are encouraged to protect their overall wellbeing by engaging in ProHealth Rewards, Protective’s platform to improve wellbeing while earning cash rewards.
Eligibility for certain benefits may vary by position in accordance with the terms of the Company’s benefit plans.
Accommodations for Applicants with a Disability: If you require an accommodation to complete the application and recruitment process due to a disability, please email eric.hess@protective.com. This information will be held in confidence and used only to determine an appropriate accommodation for the application and recruitment process.
Please note that the above email is solely for individuals with disabilities requesting an accommodation. General employment questions should not be sent through this process.
We are proud to be an equal opportunity employer committed to being inclusive and attracting, retaining, and growing an inclusive workforce.
See all 17,582+ Senior Mlops Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Senior Mlops Engineer roles.
Get Access To All JobsTips for Finding Visa Sponsorship as a Senior Mlops Engineer
Target cap-exempt employers first
Universities, nonprofit research institutions, and affiliated organizations can file H-1B petitions outside the annual lottery. For MLOps roles, these employers often run ML infrastructure teams and sponsor year-round without the April cap-subject filing window.
Document your specialized tech stack
USCIS approves H-1B petitions when the role requires a specific degree field. List every tool you work with, such as Kubeflow, MLflow, or Vertex AI, and connect each to how it demands specialized academic training beyond a general computer science background.
Use O-1A as a backup if you have a strong record
If you have published research, conference presentations, open-source contributions with significant adoption, or awards in machine learning, you may qualify for O-1A extraordinary ability. There is no lottery and no annual cap for this category.
Ask about L-1A and L-1B eligibility if you have an overseas employer
If your current employer has a U.S. office, an L-1B intracompany transfer for specialized knowledge is often faster than H-1B. MLOps engineers with proprietary internal platform knowledge frequently qualify. No lottery and no prevailing wage requirement for L-1B.
Clarify sponsorship scope during the offer stage
Some employers cover only the I-129 filing fee, not premium processing or legal fees. Confirm in writing what the employer will pay and whether they will support green card sponsorship after one year, which is common for senior engineering roles.
Browse verified sponsoring employers on Migrate Mate
Not every job listing makes sponsorship status obvious. Migrate Mate filters roles by verified sponsorship willingness, so you can focus applications on Senior MLOps positions where the employer has an active track record of filing H-1B petitions.
Frequently Asked Questions
Does a Senior MLOps Engineer role qualify as an H-1B specialty occupation?
Yes. Senior MLOps Engineer consistently qualifies as a specialty occupation because the position normally requires at least a bachelor's degree in computer science, software engineering, or a closely related field. USCIS looks at whether the degree requirement is standard for the industry. DOL LCA disclosure data shows thousands of approved H-1B visa petitions under MLOps and related ML infrastructure titles each year, confirming that employers and adjudicators treat the role as qualifying.
What degree do I need for H-1B sponsorship as an MLOps Engineer?
A bachelor's degree or higher in computer science, software engineering, mathematics, or a directly related technical field is the standard requirement. A degree in an unrelated field, even combined with strong MLOps experience, can complicate approval because USCIS requires the degree field to correspond to the role's duties. If your degree is adjacent rather than exact, an immigration attorney can build a theoretical argument using coursework relevance, but it adds risk. Equivalent experience, at the ratio of three years of work per one year of education, may substitute for a degree in some cases.
How likely is H-1B approval for an MLOps Engineer, and what are the main denial risks?
Approval rates for software and ML engineering roles are high relative to other occupations, but Requests for Evidence remain common when job duties are broadly written or the degree field is ambiguous. The most frequent RFE trigger for MLOps roles is a job description that reads as general software development rather than specialized ML infrastructure. Petitions with detailed duty descriptions linking specific tools and workflows to degree-level knowledge fare significantly better. Premium processing, which currently adjudicates within 15 business days, reduces uncertainty and is worth requesting for senior hires.
Where can I find Senior MLOps Engineer jobs that sponsor visas?
Migrate Mate is the recommended starting point. The platform lists Senior MLOps Engineer roles from employers with a verified sponsorship track record, so you are not guessing at sponsorship willingness from a standard job posting. Large tech companies, cloud platform teams at AWS, Google, and Microsoft, as well as AI-focused startups with institutional backing, are the most active sponsors in this category. Filtering by sponsorship status before applying saves significant time during a job search.
Can I stay in the U.S. and change MLOps employers if my H-1B is already approved?
Yes, H-1B portability allows you to start work with a new employer as soon as the new H-1B petition is filed, without waiting for approval, provided you have been in valid H-1B status and the new petition is non-frivolous. Your new employer files a fresh I-129 petition. You do not re-enter the lottery if you already hold H-1B status. This makes senior engineering roles with multiple competing offers more flexible than many candidates realize.
What is the prevailing wage requirement for sponsored Senior 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.