STEM OPT Machine Learning Research Jobs
Machine Learning Research roles at E-Verify-enrolled employers qualify for the 24-month STEM OPT extension, giving you up to 36 months of F-1 work authorization. Eligible degrees span computer science, statistics, electrical engineering, and related STEM CIP codes. Your employer must file a formal I-983 training plan with your DSO before your extension begins.
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Get Access To All JobsSUMMARY
As a Senior Applied ML Engineer on the Applied AI team at Databricks, you will use machine learning, scheduling, and optimization algorithms to maximize the efficiency and performance of our infrastructure. Your work will span the entire stack—from cluster management down to query compilation. You will solve complex, high-impact engineering problems to deliver highly optimized, cost-effective workloads for our customers.
IMPACT YOU WILL HAVE
- Accelerate Serverless Growth: Drive the scaling and efficiency of Databricks serverless compute products through advanced optimization techniques.
- Build Systems: Design end-to-end ML4Sys solutions from the ground up within a lean team of domain experts to support.
- Shape Strategy: Define the roadmap for applied ML investments by collaborating with engineering and product leaders across Databricks.
- Drive Deployment: Architect, train, and deploy state-of-the-art models that directly improve product performance and cost efficiency.
- Scale Infrastructure: Build robust ML pipelines, data processing layers, model serving components, and production monitoring systems to help scale.
- Innovate: Research and implement novel modeling techniques tailored specifically to computer systems and distributed environments.
MINIMUM QUALIFICATIONS
- Education: Background in Computer Science and Master's degree in Machine Learning, Data Science, or a related computational field (AI, Bioinformatics, EE, Physics, etc).
- ML Experience: Strong background in building, training, and deploying machine learning models in production.
- Infrastructure Knowledge: Practical familiarity with cloud computing, distributed systems, and modern data processing frameworks.
- Core Coding: Proficiency in Python, Scala, or Java.
PREFERRED SKILLS
- Advanced Education: PhD in AI, Data Science, or a related technical discipline.
- Industry Experience: 4+ years of machine learning engineering experience in high-velocity, high-growth environment.
- Systems Domain: Strong understanding of computer architecture, distributed computing, cloud compute, database internals, or networking.
- Optimization: Experience with operations research, forecasting, markov decision processes, or other optimization algorithms for sequential decision making.
- Scale: Proven track record of optimizing large-scale distributed systems or cloud infrastructure via data-driven approaches.
PAY RANGE TRANSPARENCY
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.
Local Pay Range
$16,000—$21,000 USD
ABOUT DATABRICKS
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
BENEFITS
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.
OUR COMMITMENT TO DIVERSITY AND INCLUSION
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
COMPLIANCE
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
SUMMARY
As a Senior Applied ML Engineer on the Applied AI team at Databricks, you will use machine learning, scheduling, and optimization algorithms to maximize the efficiency and performance of our infrastructure. Your work will span the entire stack—from cluster management down to query compilation. You will solve complex, high-impact engineering problems to deliver highly optimized, cost-effective workloads for our customers.
IMPACT YOU WILL HAVE
- Accelerate Serverless Growth: Drive the scaling and efficiency of Databricks serverless compute products through advanced optimization techniques.
- Build Systems: Design end-to-end ML4Sys solutions from the ground up within a lean team of domain experts to support.
- Shape Strategy: Define the roadmap for applied ML investments by collaborating with engineering and product leaders across Databricks.
- Drive Deployment: Architect, train, and deploy state-of-the-art models that directly improve product performance and cost efficiency.
- Scale Infrastructure: Build robust ML pipelines, data processing layers, model serving components, and production monitoring systems to help scale.
- Innovate: Research and implement novel modeling techniques tailored specifically to computer systems and distributed environments.
MINIMUM QUALIFICATIONS
- Education: Background in Computer Science and Master's degree in Machine Learning, Data Science, or a related computational field (AI, Bioinformatics, EE, Physics, etc).
- ML Experience: Strong background in building, training, and deploying machine learning models in production.
- Infrastructure Knowledge: Practical familiarity with cloud computing, distributed systems, and modern data processing frameworks.
- Core Coding: Proficiency in Python, Scala, or Java.
PREFERRED SKILLS
- Advanced Education: PhD in AI, Data Science, or a related technical discipline.
- Industry Experience: 4+ years of machine learning engineering experience in high-velocity, high-growth environment.
- Systems Domain: Strong understanding of computer architecture, distributed computing, cloud compute, database internals, or networking.
- Optimization: Experience with operations research, forecasting, markov decision processes, or other optimization algorithms for sequential decision making.
- Scale: Proven track record of optimizing large-scale distributed systems or cloud infrastructure via data-driven approaches.
PAY RANGE TRANSPARENCY
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.
Local Pay Range
$16,000—$21,000 USD
ABOUT DATABRICKS
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
BENEFITS
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.
OUR COMMITMENT TO DIVERSITY AND INCLUSION
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
COMPLIANCE
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
See all 741+ STEM OPT Machine Learning Research Jobs
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Get Access To All JobsTips for Finding STEM OPT Authorization in Machine Learning Research
Verify your CIP code before applying
Check that your degree's Classification of Instructional Programs code appears on the USCIS STEM Designated Degree Program List. Computer science, statistics, and applied mathematics codes typically qualify, but interdisciplinary programs sometimes don't. Confirm with your DSO before targeting roles.
Search employers through Migrate Mate first
Filter your Machine Learning Research job search on Migrate Mate to surface employers with verified E-Verify enrollment. This cuts out the manual legwork of cross-checking each company before you apply and saves you from pursuing dead-end opportunities.
Confirm E-Verify enrollment before accepting any offer
Ask your hiring contact directly whether the employer is enrolled in E-Verify and request their E-Verify Company ID number. An employer that can't provide this cannot legally employ STEM OPT students, regardless of how willing they are to support your extension.
Draft your I-983 training plan before your start date
USCIS requires a completed I-983 on file with your DSO before your STEM OPT extension activates. For Machine Learning Research roles, map specific projects and deliverables to learning objectives that align with your STEM degree field. Generic plans get rejected.
Target research labs with existing OPT infrastructure
University-affiliated research centers, national labs, and large tech R&D divisions process STEM OPT extensions regularly and have HR staff familiar with the I-983 requirements. First-time STEM OPT employers often cause delays because they're unfamiliar with their obligations under the training plan.
Use O*NET to frame your role's specialty occupation credentials
Pull the Machine Learning Research occupation profile from O*NET and match your degree field to the listed knowledge and skills requirements. This documentation strengthens your case if your employer or DSO needs to justify how your degree directly relates to the role.
Frequently Asked Questions
Does a Machine Learning Research role qualify for the STEM OPT extension?
Yes, provided your degree falls under a STEM-designated CIP code and the role directly applies skills from that field. Machine Learning Research positions typically satisfy this because they require quantitative reasoning, algorithm development, and statistical modeling rooted in computer science, mathematics, or engineering disciplines. Confirm your specific degree's eligibility with your DSO using the USCIS STEM Designated Degree Program List.
What E-Verify obligation does my employer have for my STEM OPT?
Your employer must be actively enrolled in E-Verify at the time your STEM OPT extension begins. Enrollment alone isn't sufficient if it lapsed. You can ask your employer to show you their E-Verify Company ID or employer participation page. If they're not enrolled, they cannot legally employ you under a STEM OPT extension, and you'd need to find an enrolled employer before your initial OPT period ends.
What goes into the I-983 training plan for a research role?
The I-983 requires a description of the research objectives, the specific skills you'll develop, how those skills connect to your STEM degree, and measurable goals your employer will evaluate. For Machine Learning Research, this typically means documenting model development cycles, experimental design responsibilities, and technical mentorship structures. Both you and a company supervisor must sign it, and your DSO must receive it before your extension is approved.
How does cap-gap protection work if I'm in a Machine Learning Research role during H-1B season?
If your employer files an H-1B visa petition on your behalf before your OPT expires and you're selected in the lottery, cap-gap automatically extends your work authorization through September 30 of that year. You can continue working in your Machine Learning Research role without interruption during this period. USCIS issues no separate document for cap-gap, your I-20 noting the cap-gap extension serves as proof of authorized status.
Where can I find Machine Learning Research jobs at E-Verify employers?
Migrate Mate filters job listings specifically for employers enrolled in E-Verify, so you're not wasting applications on companies that can't support your STEM OPT extension. Machine Learning Research roles at qualifying employers span university research divisions, national laboratories, and technology companies with active R&D programs. Searching through Migrate Mate surfaces only employers who meet the E-Verify requirement before you apply.