AI ML Engineering Visa Sponsorship Jobs in Maryland
Maryland's AI and ML engineering sector is anchored by federal contractors, biotech firms, and cybersecurity companies concentrated around the Baltimore-Washington corridor. Employers like Leidos, SAIC, Northrop Grumman, and Johns Hopkins Applied Physics Laboratory actively hire for these roles, with many positions requiring visa sponsorship for international candidates.
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Get Access To All JobsINTRODUCTION
Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).
Benefits We Offer:
- 100% Medical, Dental & Vision Coverage for Employees
- Paid Time Off and Paid Holidays
- 401K match up to 5%
- Educational Benefits for Career Growth
- Employee Referral Bonus
- Flexible Spending Accounts:
- Healthcare (FSA)
- Parking Reimbursement Account (PRK)
- Dependent Care Assistant Program (DCAP)
- Transportation Reimbursement Account (TRN)
POSITION OVERVIEW
The Data Scientist Fellow will develop computational models to predict and optimize organoid growth and differentiation protocols in support of the SOM Center. The incumbent will apply advanced machine learning techniques to organoid standardization and contribute to the development of predictive models for tissue engineering applications.
KEY RESPONSIBILITIES
- Model development. Design and implement machine learning models that predict organoid development outcomes based on protocol parameters, environmental conditions, and molecular characterization data.
- In silico simulation. Develop in silico models that correspond to organoid growth, maturation, and characterize phenotype while identifying optimal conditions for reproducible organoid generation.
- Feedback systems. Establish feedback loops between experimental validation and computational prediction in order to iteratively refine and understand protocol standardization.
- Interdisciplinary collaboration. Work with experimental teams to design characterization and validation experiments and with bioinformatics scientists to integrate multi-modal datasets.
REQUIRED QUALIFICATIONS
- Education. Doctoral degree (PhD) in computer science, engineering, applied mathematics, or a related field, with demonstrated experience in AI/ML model development.
- Programming. Strong programming proficiency in Python, R, or comparable languages, together with experience using machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
- Applied experience. Prior experience applying computational methods in biological laboratory settings, including working knowledge of experimental design principles and biological data types.
PREFERRED QUALIFICATIONS
- Experience with organoid systems or tissue engineering applications.
- Knowledge of differential equations and systems biology modeling, and experience with deep learning approaches for biological applications.
- Familiarity with cloud computing platforms and containerization technologies.
DISCLAIMER:
The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed. The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.
Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com
This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location.
Salary Range: $90,000 USD - $100,000 USD
INTRODUCTION
Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).
Benefits We Offer:
- 100% Medical, Dental & Vision Coverage for Employees
- Paid Time Off and Paid Holidays
- 401K match up to 5%
- Educational Benefits for Career Growth
- Employee Referral Bonus
- Flexible Spending Accounts:
- Healthcare (FSA)
- Parking Reimbursement Account (PRK)
- Dependent Care Assistant Program (DCAP)
- Transportation Reimbursement Account (TRN)
POSITION OVERVIEW
The Data Scientist Fellow will develop computational models to predict and optimize organoid growth and differentiation protocols in support of the SOM Center. The incumbent will apply advanced machine learning techniques to organoid standardization and contribute to the development of predictive models for tissue engineering applications.
KEY RESPONSIBILITIES
- Model development. Design and implement machine learning models that predict organoid development outcomes based on protocol parameters, environmental conditions, and molecular characterization data.
- In silico simulation. Develop in silico models that correspond to organoid growth, maturation, and characterize phenotype while identifying optimal conditions for reproducible organoid generation.
- Feedback systems. Establish feedback loops between experimental validation and computational prediction in order to iteratively refine and understand protocol standardization.
- Interdisciplinary collaboration. Work with experimental teams to design characterization and validation experiments and with bioinformatics scientists to integrate multi-modal datasets.
REQUIRED QUALIFICATIONS
- Education. Doctoral degree (PhD) in computer science, engineering, applied mathematics, or a related field, with demonstrated experience in AI/ML model development.
- Programming. Strong programming proficiency in Python, R, or comparable languages, together with experience using machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
- Applied experience. Prior experience applying computational methods in biological laboratory settings, including working knowledge of experimental design principles and biological data types.
PREFERRED QUALIFICATIONS
- Experience with organoid systems or tissue engineering applications.
- Knowledge of differential equations and systems biology modeling, and experience with deep learning approaches for biological applications.
- Familiarity with cloud computing platforms and containerization technologies.
DISCLAIMER:
The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed. The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.
Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com
This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location.
Salary Range: $90,000 USD - $100,000 USD
AI ML Engineering Job Roles in Maryland
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Search AI ML Engineering Jobs in MarylandAI ML Engineering Jobs in Maryland: Frequently Asked Questions
Which companies sponsor visas for AI ML engineers in Maryland?
Federal contractors and defense technology firms are among the most active visa sponsors for AI and ML engineers in Maryland. Companies like Leidos, SAIC, Northrop Grumman, Booz Allen Hamilton, and Peraton regularly file H-1B visa petitions for these roles. Biotech and health tech employers in the Baltimore area, including those connected to Johns Hopkins and the University of Maryland system, also sponsor international candidates for AI and ML positions.
Which visa types are most common for AI ML engineering roles in Maryland?
The H-1B is the most common visa category for AI and ML engineers in Maryland, as these roles typically qualify as specialty occupations requiring at least a bachelor's degree in computer science, data science, or a related field. Candidates already in the U.S. on F-1 OPT or STEM OPT may work while an employer files an H-1B petition. Some research-focused positions at universities or affiliated labs may also be eligible for J-1 visa or O-1 visa categories depending on the candidate's qualifications.
Which cities in Maryland have the most AI ML engineering sponsorship jobs?
The Baltimore-Washington corridor concentrates the majority of AI and ML engineering sponsorship opportunities in Maryland. Bethesda, Rockville, and Silver Spring in Montgomery County are particularly active, given the density of federal agencies, contractors, and life sciences companies. Baltimore itself has a growing tech presence tied to its university ecosystem. Greenbelt and College Park also see demand, partly due to proximity to NASA Goddard and the University of Maryland.
How to find ai ml engineering visa sponsorship jobs in Maryland?
Migrate Mate is built specifically for international job seekers and filters AI and ML engineering roles in Maryland by visa sponsorship availability, so you're not sorting through listings that won't support international candidates. The platform is useful for identifying which Maryland employers are actively sponsoring at a given time, particularly among the federal contractor and biotech clusters that drive most of the state's demand for these roles.
Are there state-specific considerations for AI ML engineers seeking sponsorship in Maryland?
Maryland's large federal contracting sector introduces a factor many candidates don't anticipate: security clearance requirements. A number of AI and ML roles with contractors like Leidos or SAIC require active U.S. security clearances, which are generally not available to non-U.S. persons. International candidates should focus on roles explicitly open to visa holders, which are more common in commercial tech, biotech, and university-affiliated research environments in the state.
What is the prevailing wage for sponsored ai ml engineering jobs in Maryland?
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.