Senior Mlops Engineer Jobs in USA with Visa Sponsorship
Senior MLOps Engineers are strong candidates for H-1B 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 JobsINTRODUCTION
Build a Safer World. TRM Labs provides blockchain analytics and AI solutions to help law enforcement and national security agencies, financial institutions, and cryptocurrency businesses detect, investigate, and disrupt crypto-related fraud and financial crime. TRM’s blockchain intelligence and AI platforms include solutions to trace the source and destination of funds, identify illicit activity, build cases, and construct an operating picture of threats. TRM is trusted by leading agencies and businesses worldwide who rely on TRM to enable a safer, more secure world for all. The AI Engineering Team is chartered with enabling next-generation AI applications, with a special focus on Large Language Models (LLMs) and agentic systems. Our mission is to build robust pipelines, high-performance infrastructure, and operational tooling that allow AI systems to be deployed with speed, safety, and scale. We manage petabyte-scale pipelines, serve models with millisecond-level latency, and provide the observability and governance needed to make AI production-ready. We’re also deeply involved in evaluating and integrating cutting-edge tools in the LLM and agent space — including open-source stacks, vector databases, evaluation frameworks, and orchestration tools that unlock TRM’s ability to innovate faster than the market.
ROLE AND RESPONSIBILITIES
As a Senior MLOps Engineer With a Focus In LLMOps, You’ll Be At The Core Of Building And Scaling The Technical Infrastructure For AI/ML Systems. You Will:
- Build reusable CI/CD workflows for model training, evaluation, and deployment — integrating Langfuse, GitHub Actions, and experiment tracking, etc.
- Automate model versioning, approval workflows, and compliance checks across environments.
- Build out a modular and scalable AI infrastructure stack — including vector databases, feature stores, model registries, and observability tooling.
- Partner with engineering and data science to embed AI models and agents into real-time applications and workflows.
- Continuously evaluate and integrate state-of-the-art AI tools (e.g. LangChain, LlamaIndex, vLLM, MLflow, BentoML, etc.).
- Drive AI reliability and governance, enabling experimentation while ensuring compliance, security, and uptime.
- Build and enhance AI/ML Model Performance.
- Ensure data accuracy, consistency and reliability, leading to better model training and inferencing.
- Deploy infrastructure to support offline and online evaluation of LLMs and agents — including regression testing, cost monitoring, and human-in-the-loop workflows.
- Enable researchers to iterate quickly by providing sandboxes, dashboards, and reproducible environments.
BASIC QUALIFICATIONS
What We’re Looking For:
- Write high-quality, maintainable software — primarily in Python, but we value engineering ability over language familiarity.
- Have a strong background in scalable infrastructure, including:
- Containerization and orchestration (e.g. Docker, Kubernetes)
- Infrastructure-as-code and deployment (e.g. Terraform, CI/CD pipelines)
- Monitoring and logging frameworks (e.g. Datadog, Prometheus, OpenTelemetry)
- Understand and implement ML Ops best practices, including:
- Model versioning and rollback strategies
- Automated evaluation and drift detection
- Scalable model and agent serving infrastructure (e.g. vLLM, Triton, BentoML)
- Deploy and maintain LLM and agentic workflows in production, including:
- Monitoring cost, latency, and performance
- Capturing traces for analysis and debugging
- Optimizing prompt/response flows with real-time data access
- Demonstrate strong ownership and pragmatism, balancing infrastructure elegance with iterative delivery and measurable impact.
PREFERRED QUALIFICATIONS
Learn About TRM Speed In This Position:
- Rapid Issue Resolution. TRM Engineers identify and resolve critical onsite issues in minutes to hours, not weeks. We create virtual war rooms, implement fixes, and share lessons with both customer stakeholders and internal teams within 48 hours.
- Navigating Bureaucracy. We anticipate and address procedural hurdles, build trust with key stakeholders, and find alternative pathways to approvals. This keeps projects moving even in complex environments.
- Efficient Knowledge Transfer. Engineers document and share updates in real time, ensuring the entire team—onsite and remote—has full visibility into plans, blockers, and resolutions. Knowledge sharing sessions and clear documentation reduce friction and accelerate delivery.
ABOUT TRM'S ENGINEERING LEVELS
Engineer: Responsible for helping to define project milestones and executing small decision decisions independently with the appropriate tradeoffs between simplicity, readability, and performance. Provides mentorship to junior engineers, and enhances operational excellence through tech debt reduction and knowledge sharing.
Senior Engineer: Successfully designs and documents system improvements and features for an OKR/project from the ground up. Consistently delivers efficient and reusable systems, optimizes team throughput with appropriate tradeoffs, mentors team members, and enhances cross-team collaboration through documentation and knowledge sharing.
Staff Engineer: Drives scoping and execution of one or more OKRs/projects that impact multiple teams. Partners with stakeholders to set the team vision and technical roadmaps for one or more products. Is a role model and mentor to the entire engineering organization. Ensures system health and quality with operational reviews, testing strategies, and monitoring rigor.
COMPENSATION
The following represents the expected range of compensation for this role:
- Individual pay is determined by skills, qualifications, experience, and location. The compensation details listed in this posting reflect the US base salary only.
- The estimated base salary range for this role is $200,000 - $220,000.
- Additionally, this role may be eligible to participate in TRM’s equity plan.
- Please note – we factor in the different costs for geographies outside the United States.
LIFE AT TRM
We are building a safer world. That promise shows up in how we work every day. TRM runs fast. Really fast. We’re a high-velocity, high-ownership team that expects clarity, follow-through, and impact. People who thrive here are energized by hard problems, experimentation, and direct feedback. If something takes months elsewhere, it often ships here in days. That pace isn’t for everyone. If you are optimizing primarily for consistent work-life balance, use the interview process to pressure-test fit. We want teammates who thrive here, not just survive here.
AI FLUENCY AT TRM
AI fluency is a baseline expectation at TRM. We believe AI meaningfully changes how top performers operate. We expect every team member to use AI to accelerate and reimagine their craft, not just automate surface tasks. At TRM, AI Fluency Means You Are Among The Top 10 Percent Of Operators In Your Function In How You Apply AI To:
- Accelerate repeatable workflows
- Structure and solve problems
- Improve output quality
- Increase speed and leverage
You will be evaluated on applied AI fluency during the interview process.
LEADERSHIP PRINCIPLES
We hire and grow against three leadership principles. They’re the standards for how we operate, treat each other, and make decisions.
- Impact-Oriented Trailblazer: We put customers first and move with speed, focus, and adaptability. We treat every plan like an experiment – test, ship, measure, and iterate quickly.
- Master Craftsperson: We care deeply about our craft. We balance speed with high standards, own outcomes end-to-end, and invest in getting better everyday.
- Inspiring Colleague: We add clarity and energy, not noise. We bring humility, candor, and a one-team mindset — giving and receiving feedback to make the team stronger.
INTERVIEWING AT TRM: HOW WE HIRE AND WHAT SUCCESS LOOKS LIKE
The impact you will have:
This work has real stakes. Depending on your role at TRM, your week might look like:
- Driving critical investigations that can’t wait for typical business hours.
- Shipping products in days when others would schedule quarters.
- Partnering with teams across time zones to deliver insights while the story is still unfolding.
- Building new solutions from first principles when the playbook doesn’t yet exist.
- Protecting victims and customers by tracing illicit activity and disrupting criminal networks.
JOIN OUR MISSION
At TRM we care deeply about our craft. We are looking for individuals who want their work to matter, who experiment with speed and rigor, and who take pride in building a safer world for billions of people. If you’re excited by TRM’s mission but don’t check every box, we encourage you to apply — we hire for slope, judgment, and the will to learn fast. TRM is a Series C company with $220M in total funding, backed by Blockchain Capital, Goldman Sachs, Bessemer, Y Combinator, Thoma Bravo, and others. Headquartered in San Francisco, TRM operates as a distributed-first company with hubs in Los Angeles, San Francisco, New York, Washington D.C., London, and Singapore.
PRIVACY POLICY AND ADDITIONAL INFORMATION
By submitting your application, you are agreeing to allow TRM to process your personal information in accordance with the TRM Privacy Policy. Our typical hiring cycles for specialized roles span 24 to 36 months. Accordingly, we retain your personal information for up to 36 months to evaluate your application and to consider you for current and future employment opportunities, unless you request earlier deletion or a different retention period is required or permitted by law. To notify TRM Labs that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this form.
RECRUITMENT AGENCIES
TRM Labs does not accept unsolicited agency resumes. Please do not forward resumes to TRM employees. TRM Labs is not responsible for any fees related to unsolicited resumes and will not pay fees to any third-party agency or company without a signed agreement.
LEARN MORE
Company Values | Interviewing | FAQs
INTRODUCTION
Build a Safer World. TRM Labs provides blockchain analytics and AI solutions to help law enforcement and national security agencies, financial institutions, and cryptocurrency businesses detect, investigate, and disrupt crypto-related fraud and financial crime. TRM’s blockchain intelligence and AI platforms include solutions to trace the source and destination of funds, identify illicit activity, build cases, and construct an operating picture of threats. TRM is trusted by leading agencies and businesses worldwide who rely on TRM to enable a safer, more secure world for all. The AI Engineering Team is chartered with enabling next-generation AI applications, with a special focus on Large Language Models (LLMs) and agentic systems. Our mission is to build robust pipelines, high-performance infrastructure, and operational tooling that allow AI systems to be deployed with speed, safety, and scale. We manage petabyte-scale pipelines, serve models with millisecond-level latency, and provide the observability and governance needed to make AI production-ready. We’re also deeply involved in evaluating and integrating cutting-edge tools in the LLM and agent space — including open-source stacks, vector databases, evaluation frameworks, and orchestration tools that unlock TRM’s ability to innovate faster than the market.
ROLE AND RESPONSIBILITIES
As a Senior MLOps Engineer With a Focus In LLMOps, You’ll Be At The Core Of Building And Scaling The Technical Infrastructure For AI/ML Systems. You Will:
- Build reusable CI/CD workflows for model training, evaluation, and deployment — integrating Langfuse, GitHub Actions, and experiment tracking, etc.
- Automate model versioning, approval workflows, and compliance checks across environments.
- Build out a modular and scalable AI infrastructure stack — including vector databases, feature stores, model registries, and observability tooling.
- Partner with engineering and data science to embed AI models and agents into real-time applications and workflows.
- Continuously evaluate and integrate state-of-the-art AI tools (e.g. LangChain, LlamaIndex, vLLM, MLflow, BentoML, etc.).
- Drive AI reliability and governance, enabling experimentation while ensuring compliance, security, and uptime.
- Build and enhance AI/ML Model Performance.
- Ensure data accuracy, consistency and reliability, leading to better model training and inferencing.
- Deploy infrastructure to support offline and online evaluation of LLMs and agents — including regression testing, cost monitoring, and human-in-the-loop workflows.
- Enable researchers to iterate quickly by providing sandboxes, dashboards, and reproducible environments.
BASIC QUALIFICATIONS
What We’re Looking For:
- Write high-quality, maintainable software — primarily in Python, but we value engineering ability over language familiarity.
- Have a strong background in scalable infrastructure, including:
- Containerization and orchestration (e.g. Docker, Kubernetes)
- Infrastructure-as-code and deployment (e.g. Terraform, CI/CD pipelines)
- Monitoring and logging frameworks (e.g. Datadog, Prometheus, OpenTelemetry)
- Understand and implement ML Ops best practices, including:
- Model versioning and rollback strategies
- Automated evaluation and drift detection
- Scalable model and agent serving infrastructure (e.g. vLLM, Triton, BentoML)
- Deploy and maintain LLM and agentic workflows in production, including:
- Monitoring cost, latency, and performance
- Capturing traces for analysis and debugging
- Optimizing prompt/response flows with real-time data access
- Demonstrate strong ownership and pragmatism, balancing infrastructure elegance with iterative delivery and measurable impact.
PREFERRED QUALIFICATIONS
Learn About TRM Speed In This Position:
- Rapid Issue Resolution. TRM Engineers identify and resolve critical onsite issues in minutes to hours, not weeks. We create virtual war rooms, implement fixes, and share lessons with both customer stakeholders and internal teams within 48 hours.
- Navigating Bureaucracy. We anticipate and address procedural hurdles, build trust with key stakeholders, and find alternative pathways to approvals. This keeps projects moving even in complex environments.
- Efficient Knowledge Transfer. Engineers document and share updates in real time, ensuring the entire team—onsite and remote—has full visibility into plans, blockers, and resolutions. Knowledge sharing sessions and clear documentation reduce friction and accelerate delivery.
ABOUT TRM'S ENGINEERING LEVELS
Engineer: Responsible for helping to define project milestones and executing small decision decisions independently with the appropriate tradeoffs between simplicity, readability, and performance. Provides mentorship to junior engineers, and enhances operational excellence through tech debt reduction and knowledge sharing.
Senior Engineer: Successfully designs and documents system improvements and features for an OKR/project from the ground up. Consistently delivers efficient and reusable systems, optimizes team throughput with appropriate tradeoffs, mentors team members, and enhances cross-team collaboration through documentation and knowledge sharing.
Staff Engineer: Drives scoping and execution of one or more OKRs/projects that impact multiple teams. Partners with stakeholders to set the team vision and technical roadmaps for one or more products. Is a role model and mentor to the entire engineering organization. Ensures system health and quality with operational reviews, testing strategies, and monitoring rigor.
COMPENSATION
The following represents the expected range of compensation for this role:
- Individual pay is determined by skills, qualifications, experience, and location. The compensation details listed in this posting reflect the US base salary only.
- The estimated base salary range for this role is $200,000 - $220,000.
- Additionally, this role may be eligible to participate in TRM’s equity plan.
- Please note – we factor in the different costs for geographies outside the United States.
LIFE AT TRM
We are building a safer world. That promise shows up in how we work every day. TRM runs fast. Really fast. We’re a high-velocity, high-ownership team that expects clarity, follow-through, and impact. People who thrive here are energized by hard problems, experimentation, and direct feedback. If something takes months elsewhere, it often ships here in days. That pace isn’t for everyone. If you are optimizing primarily for consistent work-life balance, use the interview process to pressure-test fit. We want teammates who thrive here, not just survive here.
AI FLUENCY AT TRM
AI fluency is a baseline expectation at TRM. We believe AI meaningfully changes how top performers operate. We expect every team member to use AI to accelerate and reimagine their craft, not just automate surface tasks. At TRM, AI Fluency Means You Are Among The Top 10 Percent Of Operators In Your Function In How You Apply AI To:
- Accelerate repeatable workflows
- Structure and solve problems
- Improve output quality
- Increase speed and leverage
You will be evaluated on applied AI fluency during the interview process.
LEADERSHIP PRINCIPLES
We hire and grow against three leadership principles. They’re the standards for how we operate, treat each other, and make decisions.
- Impact-Oriented Trailblazer: We put customers first and move with speed, focus, and adaptability. We treat every plan like an experiment – test, ship, measure, and iterate quickly.
- Master Craftsperson: We care deeply about our craft. We balance speed with high standards, own outcomes end-to-end, and invest in getting better everyday.
- Inspiring Colleague: We add clarity and energy, not noise. We bring humility, candor, and a one-team mindset — giving and receiving feedback to make the team stronger.
INTERVIEWING AT TRM: HOW WE HIRE AND WHAT SUCCESS LOOKS LIKE
The impact you will have:
This work has real stakes. Depending on your role at TRM, your week might look like:
- Driving critical investigations that can’t wait for typical business hours.
- Shipping products in days when others would schedule quarters.
- Partnering with teams across time zones to deliver insights while the story is still unfolding.
- Building new solutions from first principles when the playbook doesn’t yet exist.
- Protecting victims and customers by tracing illicit activity and disrupting criminal networks.
JOIN OUR MISSION
At TRM we care deeply about our craft. We are looking for individuals who want their work to matter, who experiment with speed and rigor, and who take pride in building a safer world for billions of people. If you’re excited by TRM’s mission but don’t check every box, we encourage you to apply — we hire for slope, judgment, and the will to learn fast. TRM is a Series C company with $220M in total funding, backed by Blockchain Capital, Goldman Sachs, Bessemer, Y Combinator, Thoma Bravo, and others. Headquartered in San Francisco, TRM operates as a distributed-first company with hubs in Los Angeles, San Francisco, New York, Washington D.C., London, and Singapore.
PRIVACY POLICY AND ADDITIONAL INFORMATION
By submitting your application, you are agreeing to allow TRM to process your personal information in accordance with the TRM Privacy Policy. Our typical hiring cycles for specialized roles span 24 to 36 months. Accordingly, we retain your personal information for up to 36 months to evaluate your application and to consider you for current and future employment opportunities, unless you request earlier deletion or a different retention period is required or permitted by law. To notify TRM Labs that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this form.
RECRUITMENT AGENCIES
TRM Labs does not accept unsolicited agency resumes. Please do not forward resumes to TRM employees. TRM Labs is not responsible for any fees related to unsolicited resumes and will not pay fees to any third-party agency or company without a signed agreement.
LEARN MORE
Company Values | Interviewing | FAQs
How to Get 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.
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Get Access To All JobsFrequently 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 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.
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