E-3 Visa Mlops Engineer Jobs
MLOps Engineer roles qualify for E-3 visa sponsorship as specialty occupations requiring a bachelor's degree in computer science, data science, or a related field. The E-3 has no lottery and no annual cap, making it a reliable path for Australian engineers pursuing U.S. roles in machine learning infrastructure and model deployment.
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Get Access To All JobsW2 Only
Title: Mlops Engineer
Duration: 6 Months + CTH
Location: Remote (1 Week Mandatory onboarding in tampa, FL expenses will be paid) (ONLY W2)
Job Description:
Essential Duties and Responsibilities:
- Design, implement, and maintain machine learning pipelines and workflows for the continuous deployment and integration of machine learning models. Optimize the pipelines for scalability, efficiency, and cost-effectiveness.
- Collaborate with data scientists and AI engineers to understand model requirements and optimize deployment processes.
- Automate the training, testing, and deployment processes for machine learning models.
- Establish and enforce best practices for version control, documentation, and code quality in ML projects.
- Monitor model performance and optimize algorithms for efficiency.
- Conduct regular maintenance and updates to deployed models.
- Collaborate with cross-functional teams to integrate machine learning solutions into business processes and applications.
- Work with go to market, product management, and IT functions as well as stakeholders in AF and its members to identify the optimal methods for model rollout and adoption.
- Maintain and optimize the cloud-based machine learning infrastructure and make recommendations for improvements.
- Manage and allocate resources effectively, including computer power and storage for model inference.
- Develop practices and utilize tools for data validation, model testing, and versioning.
- Troubleshoot and resolve machine learning operational issues.
- Document processes, workflows, and best practices for ML Operations.
- Provide technical leadership and mentorship to junior data team members.
Additional Duties and Responsibilities
- Support data observability efforts to ensure the data continuum and enforce governance standards.
- Other duties assigned by manager or project needs.
Qualifications
- Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, or a related field.
- Minimum of 6 years of experience in data science, machine learning, data management, data governance, or related role.
- Minimum of 6 years as a MLOps Engineer or in a similar role.
Technical Skills:
- Working knowledge of cloud services (i.e., MS Azure, AWS, Google Cloud).
- Experience with AI tools, such as MS Azure ML, Snowflake, Databricks, CortexAI, Dataiku.
- Deep understanding of data science principles, algorithms, and tools.
- Strong knowledge of data governance, data security, and compliance practices.
- Proficiency in programming languages such as Python, R, or Java.
- Experience with containerization tools like Docker and orchestration tools like Kubernetes.
- Proficiency in ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Working knowledge of CI/CD pipelines, DevOps practices, and automation frameworks.
- Deep understanding of data engineering concepts and tools.
- Familiarity with data visualization and reporting tools (e.g., Webfocus, Power BI).
Soft Skills:
- Excellent analytical and problem-solving abilities.
- Strong communication and interpersonal skills to collaborate with cross-functional teams.
- Ability to lead projects and mentor junior staff.
- Auto Insurance claims industry experience preferred.
W2 Only
Title: Mlops Engineer
Duration: 6 Months + CTH
Location: Remote (1 Week Mandatory onboarding in tampa, FL expenses will be paid) (ONLY W2)
Job Description:
Essential Duties and Responsibilities:
- Design, implement, and maintain machine learning pipelines and workflows for the continuous deployment and integration of machine learning models. Optimize the pipelines for scalability, efficiency, and cost-effectiveness.
- Collaborate with data scientists and AI engineers to understand model requirements and optimize deployment processes.
- Automate the training, testing, and deployment processes for machine learning models.
- Establish and enforce best practices for version control, documentation, and code quality in ML projects.
- Monitor model performance and optimize algorithms for efficiency.
- Conduct regular maintenance and updates to deployed models.
- Collaborate with cross-functional teams to integrate machine learning solutions into business processes and applications.
- Work with go to market, product management, and IT functions as well as stakeholders in AF and its members to identify the optimal methods for model rollout and adoption.
- Maintain and optimize the cloud-based machine learning infrastructure and make recommendations for improvements.
- Manage and allocate resources effectively, including computer power and storage for model inference.
- Develop practices and utilize tools for data validation, model testing, and versioning.
- Troubleshoot and resolve machine learning operational issues.
- Document processes, workflows, and best practices for ML Operations.
- Provide technical leadership and mentorship to junior data team members.
Additional Duties and Responsibilities
- Support data observability efforts to ensure the data continuum and enforce governance standards.
- Other duties assigned by manager or project needs.
Qualifications
- Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, or a related field.
- Minimum of 6 years of experience in data science, machine learning, data management, data governance, or related role.
- Minimum of 6 years as a MLOps Engineer or in a similar role.
Technical Skills:
- Working knowledge of cloud services (i.e., MS Azure, AWS, Google Cloud).
- Experience with AI tools, such as MS Azure ML, Snowflake, Databricks, CortexAI, Dataiku.
- Deep understanding of data science principles, algorithms, and tools.
- Strong knowledge of data governance, data security, and compliance practices.
- Proficiency in programming languages such as Python, R, or Java.
- Experience with containerization tools like Docker and orchestration tools like Kubernetes.
- Proficiency in ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Working knowledge of CI/CD pipelines, DevOps practices, and automation frameworks.
- Deep understanding of data engineering concepts and tools.
- Familiarity with data visualization and reporting tools (e.g., Webfocus, Power BI).
Soft Skills:
- Excellent analytical and problem-solving abilities.
- Strong communication and interpersonal skills to collaborate with cross-functional teams.
- Ability to lead projects and mentor junior staff.
- Auto Insurance claims industry experience preferred.
See all E-3 Visa Mlops Engineer Jobs
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Get Access To All JobsTips for Finding E-3 Visa Sponsorship as a Mlops Engineer
Frame your degree for specialty occupation
E-3 visa eligibility hinges on your degree matching the role. A computer science or data engineering degree maps cleanly, but if yours is in a related field like mathematics or statistics, document how your coursework and experience directly support MLOps work.
Target employers with active ML infrastructure teams
Companies running large-scale model deployment pipelines are most likely to understand E-3 sponsorship requirements. Focus your search on organizations with dedicated platform or ML engineering teams, not those where MLOps is a secondary responsibility shared across roles.
Clarify your Australian citizenship early in screening
Many U.S. recruiters conflate visa sponsorship with the H-1B lottery and assume it takes months. Tell them upfront that your E-3 requires no lottery, no cap, and can be processed in weeks. This removes a common reason offers get stalled or withdrawn.
Confirm the job description specifies a required degree
The DOL requires your LCA job posting to list a specific degree as required, not preferred. If the role description says 'bachelor's preferred,' ask HR to revise it before the LCA is filed. A 'preferred' qualification can undermine your specialty occupation determination.
Use Migrate Mate's E-3 filing service after your offer
Once you have a signed offer, use Migrate Mate's E-3 filing service to handle your LCA and visa paperwork. The service manages DOL certification, DS-160 preparation, and consulate appointment coordination so you and your employer aren't navigating the process alone.
Check E-Verify enrollment before your start date
If your MLOps role involves handling certain federal contracts or sensitive data systems, your employer may be required to be enrolled in E-Verify. Confirm enrollment status before you accept, as unenrolled employers may face onboarding delays that affect your start date.
E-3 Visa Mlops Engineer: Frequently Asked Questions
How do I find MLOps Engineer jobs with E-3 visa sponsorship?
Migrate Mate is built specifically for this search. It filters MLOps Engineer roles by E-3 sponsorship readiness, so you're not sifting through listings from employers unfamiliar with the visa. Standard job searches surface roles without any indication of whether the hiring team understands E-3 requirements or has sponsored Australians before.
How much does it cost to get an E-3 visa?
Migrate Mate's E-3 filing service covers the entire process for $499, including the Labor Condition Application, visa document preparation, and consulate appointment guidance. Traditional immigration lawyers charge $2,000–$5,000+ for the same work. The E-3 has less paperwork than most work visas, so paying thousands for legal help is usually unnecessary.
Does an MLOps Engineer role qualify as a specialty occupation for E-3?
Yes. MLOps Engineer roles require a theoretical and practical application of computer science, systems engineering, or data engineering, and typically require at least a bachelor's degree in a relevant field. USCIS evaluates specialty occupation on a case-by-case basis, but roles involving model lifecycle management, CI/CD pipeline design, and infrastructure-as-code are well-supported by the definition.
How does the E-3 compare to H-1B for MLOps Engineers in the United States?
For Australian MLOps Engineers, the E-3 is significantly more predictable. The H-1B is subject to an annual lottery with a roughly 25% selection rate, meaning most registrants are not selected. The E-3 has a 10,500 annual cap that has never been exhausted, requires no lottery, and can typically be processed within weeks of a job offer. You can start work after consulate approval without waiting for a fiscal year start date.
Can I switch MLOps Engineer employers while on an E-3 visa?
Yes, but you need a new E-3 for each employer. Your E-3 is employer-specific, so if you change roles or companies, your new employer must file a fresh LCA with the DOL and you'll need to attend a new consulate appointment. There's no portability provision like some other visa categories, so plan for a processing gap between your last day and your new start date.