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 JobsHiring: Machine Learning Engineer
Experience: 0–2 Years
Job Summary
We are looking for a motivated and analytical Machine Learning Engineer to develop, implement, and optimize machine learning models for real-world applications. The ideal candidate should have a strong foundation in Python programming, machine learning algorithms, statistical modeling, and data processing. This role is suitable for master's graduates with hands-on experience through academic projects, internships, research, or practical implementation of machine learning solutions.
Key Responsibilities
- Design, develop, train, and optimize machine learning models for predictive analytics and intelligent applications.
- Perform data preprocessing, feature engineering, and exploratory data analysis on structured and unstructured datasets.
- Implement supervised and unsupervised machine learning algorithms.
- Evaluate model performance and improve accuracy using appropriate validation techniques.
- Work with deep learning frameworks to develop and experiment with neural network models.
- Collaborate with engineering and data science teams to integrate machine learning models into applications.
- Develop and maintain efficient data processing and machine learning pipelines.
- Document model development, testing procedures, and technical findings.
Required Technical Skills
- Proficiency in Python programming.
- Working knowledge of machine learning algorithms and statistical modeling.
- Familiarity with Scikit-learn, TensorFlow, or PyTorch.
- Experience with Pandas and NumPy for data manipulation and analysis.
- Understanding of supervised learning, unsupervised learning, and model evaluation techniques.
- Knowledge of SQL and database management concepts.
- Familiarity with Git and version control systems.
Preferred Qualifications
- Master's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, or a related technical discipline.
- 0–2 years of experience in machine learning, artificial intelligence, or data science.
- Academic projects, internships, research experience, or personal projects involving machine learning are considered relevant experience.
- Exposure to cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform is a plus.
- Familiarity with Docker, Kubernetes, MLOps, or machine learning model deployment is an advantage.
Hiring: Machine Learning Engineer
Experience: 0–2 Years
Job Summary
We are looking for a motivated and analytical Machine Learning Engineer to develop, implement, and optimize machine learning models for real-world applications. The ideal candidate should have a strong foundation in Python programming, machine learning algorithms, statistical modeling, and data processing. This role is suitable for master's graduates with hands-on experience through academic projects, internships, research, or practical implementation of machine learning solutions.
Key Responsibilities
- Design, develop, train, and optimize machine learning models for predictive analytics and intelligent applications.
- Perform data preprocessing, feature engineering, and exploratory data analysis on structured and unstructured datasets.
- Implement supervised and unsupervised machine learning algorithms.
- Evaluate model performance and improve accuracy using appropriate validation techniques.
- Work with deep learning frameworks to develop and experiment with neural network models.
- Collaborate with engineering and data science teams to integrate machine learning models into applications.
- Develop and maintain efficient data processing and machine learning pipelines.
- Document model development, testing procedures, and technical findings.
Required Technical Skills
- Proficiency in Python programming.
- Working knowledge of machine learning algorithms and statistical modeling.
- Familiarity with Scikit-learn, TensorFlow, or PyTorch.
- Experience with Pandas and NumPy for data manipulation and analysis.
- Understanding of supervised learning, unsupervised learning, and model evaluation techniques.
- Knowledge of SQL and database management concepts.
- Familiarity with Git and version control systems.
Preferred Qualifications
- Master's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, or a related technical discipline.
- 0–2 years of experience in machine learning, artificial intelligence, or data science.
- Academic projects, internships, research experience, or personal projects involving machine learning are considered relevant experience.
- Exposure to cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform is a plus.
- Familiarity with Docker, Kubernetes, MLOps, or machine learning model deployment is an advantage.
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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.