STEM OPT ML Engineer Jobs
ML Engineer roles qualify for STEM OPT because they fall under computer science and engineering CIP codes, giving you up to 24 months of additional work authorization beyond your initial OPT period. Your employer must be enrolled in E-Verify, and you'll need an approved I-983 training plan tied to a qualifying STEM degree.
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Get Access To All JobsINTRODUCTION
When you’re the best, we’re the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves. We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future.
SUMMARY
In this role, you will develop and support machine learning and data-driven solutions that address business and operational challenges within enterprise platforms, including Palantir. You will collaborate with cross-functional teams to build scalable AI/ML workflows, contribute to Operational Database (ODB) 2.0 transformation initiatives and Metrics Ontology methodology work, and support the full machine learning lifecycle from data preparation through deployment and monitoring. You will analyze complex datasets, develop production-ready solutions, and apply best practices for data governance, security, and model validation.
Responsibilities:
- Develop, test, and deploy machine learning models to support business and operational use cases.
- Build and maintain data pipelines to ingest, process, and transform structured and unstructured data.
- Perform exploratory data analysis to identify trends, patterns, and data quality issues.
- Write clean, efficient, and maintainable code for data processing and model development.
- Support end-to-end machine learning lifecycle activities, including data preparation, model evaluation, deployment, and performance monitoring.
- Develop workflows and integrate data sources within enterprise platforms, including Palantir.
- Collaborate with data engineers, analysts, and clients to translate business requirements into technical solutions.
- Document code, methodologies, and processes to support reproducibility and compliance standards.
- Apply best practices for data governance, security, and model validation.
- Troubleshoot and improve model and pipeline performance within production environments.
QUALIFICATIONS
- Relevant degree preferred.
- No prior experience required.
- Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or related field required.
- Proficiency in Python and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch highly preferred.
- Working knowledge of SQL and experience with relational databases highly preferred.
- Understanding of machine learning concepts, including regression, classification, clustering, and model evaluation.
- Familiarity with software engineering fundamentals, including version control, testing, and debugging.
- Exposure to cloud or data platforms such as AWS, Azure, or Palantir preferred.
- Strong analytical, problem-solving, written, and verbal communication skills.
- Ability to work collaboratively in a team environment while managing multiple priorities.
ESTIMATED HIRING RANGE:
At Vizient, we consider skills, experience, and organizational needs in our compensation approach. Geographic factors may adjust the range estimate and hires typically fall below the top range. Compensation decisions are tailored to individual circumstances. The current salary range for this role is $68,500.00 to $116,300.00. This position is also incentive eligible.
Vizient has a comprehensive benefits plan! Please view our benefits here:
http://www.vizientinc.com/about-us/careers
Equal Opportunity Employer: Females/Minorities/Veterans/Individuals with Disabilities
The Company is committed to equal employment opportunity to all employees and applicants without regard to race, religion, color, gender identity, ethnicity, age, national origin, sexual orientation, disability status, veteran status or any other category protected by applicable law.
INTRODUCTION
When you’re the best, we’re the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves. We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future.
SUMMARY
In this role, you will develop and support machine learning and data-driven solutions that address business and operational challenges within enterprise platforms, including Palantir. You will collaborate with cross-functional teams to build scalable AI/ML workflows, contribute to Operational Database (ODB) 2.0 transformation initiatives and Metrics Ontology methodology work, and support the full machine learning lifecycle from data preparation through deployment and monitoring. You will analyze complex datasets, develop production-ready solutions, and apply best practices for data governance, security, and model validation.
Responsibilities:
- Develop, test, and deploy machine learning models to support business and operational use cases.
- Build and maintain data pipelines to ingest, process, and transform structured and unstructured data.
- Perform exploratory data analysis to identify trends, patterns, and data quality issues.
- Write clean, efficient, and maintainable code for data processing and model development.
- Support end-to-end machine learning lifecycle activities, including data preparation, model evaluation, deployment, and performance monitoring.
- Develop workflows and integrate data sources within enterprise platforms, including Palantir.
- Collaborate with data engineers, analysts, and clients to translate business requirements into technical solutions.
- Document code, methodologies, and processes to support reproducibility and compliance standards.
- Apply best practices for data governance, security, and model validation.
- Troubleshoot and improve model and pipeline performance within production environments.
QUALIFICATIONS
- Relevant degree preferred.
- No prior experience required.
- Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or related field required.
- Proficiency in Python and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch highly preferred.
- Working knowledge of SQL and experience with relational databases highly preferred.
- Understanding of machine learning concepts, including regression, classification, clustering, and model evaluation.
- Familiarity with software engineering fundamentals, including version control, testing, and debugging.
- Exposure to cloud or data platforms such as AWS, Azure, or Palantir preferred.
- Strong analytical, problem-solving, written, and verbal communication skills.
- Ability to work collaboratively in a team environment while managing multiple priorities.
ESTIMATED HIRING RANGE:
At Vizient, we consider skills, experience, and organizational needs in our compensation approach. Geographic factors may adjust the range estimate and hires typically fall below the top range. Compensation decisions are tailored to individual circumstances. The current salary range for this role is $68,500.00 to $116,300.00. This position is also incentive eligible.
Vizient has a comprehensive benefits plan! Please view our benefits here:
http://www.vizientinc.com/about-us/careers
Equal Opportunity Employer: Females/Minorities/Veterans/Individuals with Disabilities
The Company is committed to equal employment opportunity to all employees and applicants without regard to race, religion, color, gender identity, ethnicity, age, national origin, sexual orientation, disability status, veteran status or any other category protected by applicable law.
See all 1,047+ STEM OPT ML Engineer Jobs
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Get Access To All JobsTips for Finding STEM OPT Authorization as a ML Engineer
Verify your CIP code matches ML Engineering
Check your degree's Classification of Instructional Programs code against the DHS STEM OPT designated degree list before applying. Computer Science (11.0701), Electrical Engineering (14.1001), and Applied Mathematics (27.0301) are common qualifying codes for ML Engineer roles.
Confirm E-Verify enrollment before accepting offers
Ask recruiters for their E-Verify company ID or check enrollment status directly through the E-Verify employer search tool. An employer not enrolled in E-Verify cannot legally support your STEM OPT extension, regardless of how eager they are to hire you.
Use Migrate Mate to filter ML Engineer roles by E-Verify status
Search ML Engineer positions on Migrate Mate to surface employers already verified for STEM OPT eligibility. This cuts the research time of manually cross-referencing job postings against E-Verify enrollment records before you invest in an application.
Build your I-983 training plan around ML deliverables
Draft your I-983 before your offer letter is finalized so your hiring manager can sign off quickly. Map specific ML Engineering tasks, such as model training pipelines and production deployment, to your STEM degree's learning objectives to satisfy USCIS review standards.
Target employers with active H-1B filing history in ML roles
Companies that regularly file H-1B visa petitions for software and ML roles have established immigration infrastructure and understand STEM OPT reporting obligations. DOL LCA disclosure data shows which employers file for ML Engineer-adjacent SOC codes year over year.
Time your STEM OPT application to cover your start date
File your STEM OPT extension with your DSO at least 90 days before your initial OPT expires. USCIS recommends submitting Form I-765 early enough that your EAD arrives before your authorization lapses, protecting your ability to start on your target date.
Frequently Asked Questions
Does an ML Engineer role qualify for the STEM OPT extension?
ML Engineer positions typically qualify when your employer maps the role to a STEM-designated SOC code, such as Software Developers (15-1252) or Computer and Information Research Scientists (15-1221), and your degree falls under a qualifying CIP code. Confirm the match with your DSO before filing. You can verify the SOC classification for ML Engineering work through O*NET.
What STEM degrees are accepted for an ML Engineer STEM OPT extension?
Degrees in Computer Science, Electrical Engineering, Applied Mathematics, Statistics, and Data Science are commonly accepted, provided they appear on the DHS STEM Designated Degree Program list under their respective CIP codes. A degree in a non-STEM field does not qualify even if your coursework included machine learning. Your DSO can confirm your specific CIP code eligibility before you apply.
How do I verify that an ML Engineer employer is enrolled in E-Verify?
Use the E-Verify employer search tool to look up any company by name before accepting an offer. Enrollment in E-Verify is a legal requirement for STEM OPT employers, not an optional benefit. If a company is not enrolled, they cannot legally employ you under the STEM OPT extension. Migrate Mate surfaces ML Engineer roles from E-Verify-enrolled employers so you can focus your search efficiently.
What goes into an I-983 training plan for an ML Engineer position?
Your I-983 must describe how the ML Engineer role provides practical training related to your STEM degree. Include specific responsibilities such as developing neural network architectures, running model validation pipelines, or deploying inference systems, and explain how each connects to your academic coursework. Both you and your employer's authorized representative must sign it, and your DSO must review and maintain it throughout your extension period.
Does cap-gap protection apply if my H-1B is selected while I work as an ML Engineer on STEM OPT?
Yes. If your employer files an H-1B petition on your behalf before your STEM OPT EAD expires, cap-gap protection automatically extends your work authorization through September 30 of that fiscal year, or until your H-1B start date of October 1, whichever comes first. You can continue working as an ML Engineer without interruption as long as the petition remains pending or approved. USCIS provides formal guidance on cap-gap eligibility on its website.