TN Visa Senior Mlops Engineer Jobs
Senior MLOps Engineers qualify for TN visa sponsorship under the USMCA's Computer Systems Analyst category, which covers roles involving the design, deployment, and optimization of machine learning infrastructure. Canadian citizens can enter at the port of entry with employer support documentation; Mexican citizens apply through consular processing. Employers prepare a support letter to initiate your TN application.
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Role summary:
Help power the infrastructure behind athenahealth’s AI platform. The Senior MLOps Engineer is a Senior Associate-level role based in Boston, MA in a hybrid work model, responsible for engineering, maintaining, and advancing centralized AI platforms that support model training, serving, monitoring, and operational reliability. This role partners across engineering, data science, and platform teams to improve platform performance, security, and availability while enabling scalable AI development and deployment. This role reports to the Senior Manager.
Team summary:
Core AI is at the center of athenahealth’s company-wide initiative to unlock the value of healthcare information through data science, machine learning, and generative AI. Working with large-scale healthcare data, the team develops platforms and capabilities that support innovative AI use cases across the business and help improve the healthcare experience for providers and patients.
The MLOps team designs, develops, deploys, monitors, and supports the cloud-based platform that powers frontier, foundational, and customized models at athenahealth. This team focuses on operational reliability, platform performance, secure delivery, and scalable engineering practices. The Senior MLOps Engineer will help build and improve the tools, infrastructure, and workflows that make it easier for teams to train, deploy, observe, and manage AI services in production. This role works closely with AI engineers, data scientists, and infrastructure partners to ensure the platform is resilient, efficient, and ready to support evolving business and technical needs.
Essential Job Responsibilities:
- Engineer and maintain centralized AI and MLOps platforms that support model training, deployment, and serving at scale.
- Ensure the availability, performance, and reliability of cloud-based ML training and inference platforms through monitoring, alerting, and proactive issue identification.
- Build automation and platform tools that improve deployment speed, service stability, and engineering confidence.
- Deploy and maintain containerized services and ML workloads in Kubernetes-based environments.
- Integrate security practices into software and infrastructure delivery workflows to support secure, reliable platform operations.
- Collaborate across engineering, infrastructure, and AI teams to support high availability, disaster recovery, and strong customer outcomes.
- Evaluate and integrate emerging AI tools and technologies from providers such as OpenAI, Anthropic, Google, Microsoft, and AWS where they align with platform needs.
- Develop microservices and platform components in public cloud environments such as AWS, Azure, or GCP.
- Use AI tools and platform capabilities in day-to-day engineering work to improve troubleshooting, automation, deployment workflows, and operational efficiency, while continuing to learn and apply new tools as they become relevant to the role.
Additional Job Responsibilities:
- Support incident response, root cause analysis, and follow-up remediation efforts.
- Document platform architecture, operational procedures, and engineering standards.
- Contribute to platform roadmap discussions and technical planning activities.
- Partner with data scientists and AI engineers to improve model training and deployment workflows.
- Assist with evaluation of new frameworks, tooling, and observability capabilities.
- Improve system visibility through dashboards, metrics, and log aggregation practices.
- Participate in design reviews and cross-team technical discussions.
- Contribute to continuous improvement of MLOps, DevOps, and SRE practices.
Expected Education & Experience:
- Bachelor’s degree in Computer Science or an equivalent field, or equivalent professional experience.
- 4 to 6 years of experience in Software Engineering, Data Engineering, MLOps, DevOps, SRE, or a related technical area.
- Strong experience with Kubernetes, including designing, deploying, and maintaining enterprise-class ML models and services.
- Proficiency in Python and experience developing microservices in public cloud environments such as AWS, Azure, or GCP.
- Experience with ML platform and infrastructure technologies such as Terraform, Spark, service mesh architectures including Istio, and cloud security practices.
- Experience deploying and maintaining Linux-based, scalable, fault-tolerant software platforms.
- Experience with Azure AI Foundry or Amazon Bedrock, and familiarity with services such as LiteLLM, LangSmith, Arize, or Braintrust.
- Experience with monitoring and observability tools such as Grafana, Prometheus, and CloudWatch.
- Experience with databases and data platforms such as Snowflake, Postgres, MySQL, Redis, and DynamoDB.
- Familiarity with CI/CD, configuration management, and orchestration tools such as Jenkins, Puppet, Bottlerocket, or Chef.
- Experience working with Data Scientists and AI Engineers, including support for model training pipelines such as Kubeflow.
Expected Compensation
$145,000 - $247,000* The base salary range shown reflects the full range for this role from minimum to maximum. At athenahealth, base pay depends on multiple factors, including job-related experience, relevant knowledge and skills, how your qualifications compare to others in similar roles, and geographical market rates. Base pay is only one part of our competitive Total Rewards package - depending on role eligibility, we offer both short and long-term incentives by way of an annual discretionary bonus plan, variable compensation plan, and equity plans.
About athenahealth
Our vision: In an industry that becomes more complex by the day, we stand for simplicity. We offer IT solutions and expert services that eliminate the daily hurdles preventing healthcare providers from focusing entirely on their patients — powered by our vision to create a thriving ecosystem that delivers accessible, high-quality, and sustainable healthcare for all.
Our company culture: Our talented employees — or athenistas, as we call ourselves — spark the innovation and passion needed to accomplish our vision. We are a diverse group of dreamers and do-ers with unique knowledge, expertise, backgrounds, and perspectives. We unite as mission-driven problem-solvers with a deep desire to achieve our vision and make our time here count. Our award-winning culture is built around shared values of inclusiveness, accountability, and support.
Our DEI commitment: Our vision of accessible, high-quality, and sustainable healthcare for all requires addressing the inequities that stand in the way. That's one reason we prioritize diversity, equity, and inclusion in every aspect of our business, from attracting and sustaining a diverse workforce to maintaining an inclusive environment for athenistas, our partners, customers and the communities where we work and serve.
What we can do for you:
Along with health and financial benefits, athenistas enjoy perks specific to each location, including commuter support, employee assistance programs, tuition assistance, employee resource groups, and collaborative workspaces — some offices even welcome dogs.
We also encourage a better work-life balance for athenistas with our flexibility. While we know in-office collaboration is critical to our vision, we recognize that not all work needs to be done within an office environment, full-time. With consistent communication and digital collaboration tools, athenahealth enables employees to find a balance that feels fulfilling and productive for each individual situation.
In addition to our traditional benefits and perks, we sponsor events throughout the year, including book clubs, external speakers, and hackathons. We provide athenistas with a company culture based on learning, the support of an engaged team, and an inclusive environment where all employees are valued.
Learn more about our culture and benefits here: athenahealth.com/careers
Location: Boston, MA
Join us as we work to create a thriving ecosystem that delivers accessible, high-quality, and sustainable healthcare for all.
Role summary:
Help power the infrastructure behind athenahealth’s AI platform. The Senior MLOps Engineer is a Senior Associate-level role based in Boston, MA in a hybrid work model, responsible for engineering, maintaining, and advancing centralized AI platforms that support model training, serving, monitoring, and operational reliability. This role partners across engineering, data science, and platform teams to improve platform performance, security, and availability while enabling scalable AI development and deployment. This role reports to the Senior Manager.
Team summary:
Core AI is at the center of athenahealth’s company-wide initiative to unlock the value of healthcare information through data science, machine learning, and generative AI. Working with large-scale healthcare data, the team develops platforms and capabilities that support innovative AI use cases across the business and help improve the healthcare experience for providers and patients.
The MLOps team designs, develops, deploys, monitors, and supports the cloud-based platform that powers frontier, foundational, and customized models at athenahealth. This team focuses on operational reliability, platform performance, secure delivery, and scalable engineering practices. The Senior MLOps Engineer will help build and improve the tools, infrastructure, and workflows that make it easier for teams to train, deploy, observe, and manage AI services in production. This role works closely with AI engineers, data scientists, and infrastructure partners to ensure the platform is resilient, efficient, and ready to support evolving business and technical needs.
Essential Job Responsibilities:
- Engineer and maintain centralized AI and MLOps platforms that support model training, deployment, and serving at scale.
- Ensure the availability, performance, and reliability of cloud-based ML training and inference platforms through monitoring, alerting, and proactive issue identification.
- Build automation and platform tools that improve deployment speed, service stability, and engineering confidence.
- Deploy and maintain containerized services and ML workloads in Kubernetes-based environments.
- Integrate security practices into software and infrastructure delivery workflows to support secure, reliable platform operations.
- Collaborate across engineering, infrastructure, and AI teams to support high availability, disaster recovery, and strong customer outcomes.
- Evaluate and integrate emerging AI tools and technologies from providers such as OpenAI, Anthropic, Google, Microsoft, and AWS where they align with platform needs.
- Develop microservices and platform components in public cloud environments such as AWS, Azure, or GCP.
- Use AI tools and platform capabilities in day-to-day engineering work to improve troubleshooting, automation, deployment workflows, and operational efficiency, while continuing to learn and apply new tools as they become relevant to the role.
Additional Job Responsibilities:
- Support incident response, root cause analysis, and follow-up remediation efforts.
- Document platform architecture, operational procedures, and engineering standards.
- Contribute to platform roadmap discussions and technical planning activities.
- Partner with data scientists and AI engineers to improve model training and deployment workflows.
- Assist with evaluation of new frameworks, tooling, and observability capabilities.
- Improve system visibility through dashboards, metrics, and log aggregation practices.
- Participate in design reviews and cross-team technical discussions.
- Contribute to continuous improvement of MLOps, DevOps, and SRE practices.
Expected Education & Experience:
- Bachelor’s degree in Computer Science or an equivalent field, or equivalent professional experience.
- 4 to 6 years of experience in Software Engineering, Data Engineering, MLOps, DevOps, SRE, or a related technical area.
- Strong experience with Kubernetes, including designing, deploying, and maintaining enterprise-class ML models and services.
- Proficiency in Python and experience developing microservices in public cloud environments such as AWS, Azure, or GCP.
- Experience with ML platform and infrastructure technologies such as Terraform, Spark, service mesh architectures including Istio, and cloud security practices.
- Experience deploying and maintaining Linux-based, scalable, fault-tolerant software platforms.
- Experience with Azure AI Foundry or Amazon Bedrock, and familiarity with services such as LiteLLM, LangSmith, Arize, or Braintrust.
- Experience with monitoring and observability tools such as Grafana, Prometheus, and CloudWatch.
- Experience with databases and data platforms such as Snowflake, Postgres, MySQL, Redis, and DynamoDB.
- Familiarity with CI/CD, configuration management, and orchestration tools such as Jenkins, Puppet, Bottlerocket, or Chef.
- Experience working with Data Scientists and AI Engineers, including support for model training pipelines such as Kubeflow.
Expected Compensation
$145,000 - $247,000* The base salary range shown reflects the full range for this role from minimum to maximum. At athenahealth, base pay depends on multiple factors, including job-related experience, relevant knowledge and skills, how your qualifications compare to others in similar roles, and geographical market rates. Base pay is only one part of our competitive Total Rewards package - depending on role eligibility, we offer both short and long-term incentives by way of an annual discretionary bonus plan, variable compensation plan, and equity plans.
About athenahealth
Our vision: In an industry that becomes more complex by the day, we stand for simplicity. We offer IT solutions and expert services that eliminate the daily hurdles preventing healthcare providers from focusing entirely on their patients — powered by our vision to create a thriving ecosystem that delivers accessible, high-quality, and sustainable healthcare for all.
Our company culture: Our talented employees — or athenistas, as we call ourselves — spark the innovation and passion needed to accomplish our vision. We are a diverse group of dreamers and do-ers with unique knowledge, expertise, backgrounds, and perspectives. We unite as mission-driven problem-solvers with a deep desire to achieve our vision and make our time here count. Our award-winning culture is built around shared values of inclusiveness, accountability, and support.
Our DEI commitment: Our vision of accessible, high-quality, and sustainable healthcare for all requires addressing the inequities that stand in the way. That's one reason we prioritize diversity, equity, and inclusion in every aspect of our business, from attracting and sustaining a diverse workforce to maintaining an inclusive environment for athenistas, our partners, customers and the communities where we work and serve.
What we can do for you:
Along with health and financial benefits, athenistas enjoy perks specific to each location, including commuter support, employee assistance programs, tuition assistance, employee resource groups, and collaborative workspaces — some offices even welcome dogs.
We also encourage a better work-life balance for athenistas with our flexibility. While we know in-office collaboration is critical to our vision, we recognize that not all work needs to be done within an office environment, full-time. With consistent communication and digital collaboration tools, athenahealth enables employees to find a balance that feels fulfilling and productive for each individual situation.
In addition to our traditional benefits and perks, we sponsor events throughout the year, including book clubs, external speakers, and hackathons. We provide athenistas with a company culture based on learning, the support of an engaged team, and an inclusive environment where all employees are valued.
Learn more about our culture and benefits here: athenahealth.com/careers
Location: Boston, MA
See all 37+ 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 TN Visa Sponsorship as a Senior Mlops Engineer
Frame your credentials around systems analysis
TN classification for MLOps roles depends on mapping your work to Computer Systems Analyst duties. Document how your role involves analyzing, designing, and implementing ML pipeline systems, not just running models or writing scripts.
Separate your ML and ops experience clearly
Employers reviewing your TN support letter need to see that your MLOps work is analytical and specialized. Break out your experience with infrastructure orchestration, model serving, and monitoring into distinct bullet points, not combined job summaries.
Target employers with recent visa filing history
Companies that have recent visa filings for similar technical roles are already familiar with sponsorship processes. Filtering by employers experienced with work visa sponsorship cuts down time spent educating hiring managers about TN requirements.
Use Migrate Mate to find verified sponsoring employers
Search Migrate Mate to identify companies actively offering TN visa sponsorship for Senior MLOps Engineer roles. The platform surfaces employers with real sponsorship history, so you're not cold-applying to companies unfamiliar with TN filing requirements.
Get your support letter drafted before the offer stage
The TN support letter must describe your specific duties, your qualifying degree, and the employer's business need. Having a draft ready lets you move quickly once an offer is made, since Canadian applicants can present at the border the same day.
Clarify Mexican TN processing timelines with your employer early
Mexican nationals require a consular appointment and face longer processing windows than Canadians. Set expectations with your hiring manager during the offer stage so your start date accounts for consulate scheduling, not just the employer's support letter preparation timeline.
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Find Senior Mlops Engineer JobsSenior Mlops Engineer TN Visa: Frequently Asked Questions
Does a Senior MLOps Engineer role qualify for TN visa sponsorship?
Yes, provided the role is classified under the Computer Systems Analyst category in the USMCA's TN occupation list. Your job duties must involve analyzing and designing ML systems, not purely operational or support tasks. A well-drafted employer support letter that ties your MLOps responsibilities to systems analysis work is what makes the classification hold up at the port of entry or consulate.
How does TN visa sponsorship for MLOps roles compare to H-1B?
TN has no lottery and no annual cap for Canadian citizens, which means you can start the process as soon as you have a job offer and employer support letter. H-1B requires winning a lottery that accepts only around one in four registrations. For a Senior MLOps Engineer with a qualifying degree and a U.S. employer willing to sponsor, TN is typically faster and more predictable than waiting on H-1B selection.
What degree does a Senior MLOps Engineer need for TN classification?
You need at least a bachelor's degree in computer science, engineering, mathematics, or a closely related technical field. The degree must connect logically to your MLOps duties. A degree in an unrelated field combined with MLOps work experience does not satisfy the Computer Systems Analyst educational requirement, so degree alignment is something to confirm before applying.
How can I find Senior MLOps Engineer jobs with TN visa sponsorship?
Migrate Mate is built specifically for this search. It lets Canadian and Mexican professionals filter for Senior MLOps Engineer roles at employers that have active TN visa sponsorship, so you can focus your applications on companies that already understand and support the process rather than spending time educating recruiters about TN requirements from scratch.
Can a Senior MLOps Engineer on TN status change employers mid-year?
Yes. TN status is employer-specific, so a change requires your new employer to prepare a support letter. Canadian citizens can present the new TN documentation at the border for same-day processing. Mexican nationals need to schedule a new consular appointment. You can start working for the new employer once the new TN is approved, not before.
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