STEM OPT AI ML Intern Jobs
AI ML Intern roles qualify for the 24-month STEM OPT extension if your degree falls under an eligible CIP code in computer science, data science, or a related STEM field. Your employer must be enrolled in E-Verify, and you'll need a signed I-983 training plan before your start date.
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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 727+ STEM OPT AI ML Intern Jobs
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Get Access To All JobsTips for Finding STEM OPT Authorization as an AI ML Intern
Verify your CIP code before applying
Check that your degree's CIP code appears on the DHS STEM Designated Degree Program List. AI and ML roles attract scrutiny when the degree field is adjacent, like information systems, so confirm the match before your DSO files the extension.
Filter employers by E-Verify enrollment status
Use the E-Verify employer search to confirm a company is actively enrolled before you apply. Internship postings rarely flag this, and discovering a mismatch after an offer is made can void your extension eligibility entirely.
Build a portfolio that maps to ML job zones
Recruiters screening STEM OPT interns for AI and ML roles compare your projects against O*NET occupation profiles. Annotate your GitHub repos with the specific tasks and tools listed in the relevant O*NET job zone to reduce screening friction.
Negotiate your I-983 training plan before signing
Request a draft I-983 from the employer during the offer stage, not after. The training plan must list specific learning objectives tied to your STEM degree, and vague plans are the most common reason DSOs delay extension approval.
Use Migrate Mate to find E-Verify enrolled employers
Search AI ML Intern roles on Migrate Mate, which filters for employers already enrolled in E-Verify. This removes the manual verification step and lets you focus your applications on companies that can legally support your STEM OPT extension.
Frequently Asked Questions
Does an AI ML Intern role qualify for the STEM OPT extension?
It qualifies if your degree's CIP code appears on the DHS STEM Designated Degree Program List and the role provides practical training directly related to that field. Degrees in computer science, electrical engineering, data science, and applied mathematics typically qualify. Your DSO confirms eligibility and files the extension through SEVIS. The internship itself must be paid and supervised by an E-Verify enrolled employer.
How do I confirm an employer is enrolled in E-Verify for my STEM OPT?
Use the E-Verify employer search tool to look up any company by name or employer identification number before accepting an offer. STEM OPT is invalid without an actively enrolled E-Verify employer, even if USCIS approves your EAD. If a startup or research lab isn't enrolled, they must complete E-Verify enrollment before your extension start date. You can also browse verified employers directly on Migrate Mate.
What goes into the I-983 training plan for an AI ML Intern position?
The I-983 must identify specific learning objectives tied to your STEM degree, list the tools and methodologies you'll use, name a designated supervisor, and include a formal evaluation schedule. For AI and ML roles, objectives should reference concrete skills like model training, data pipeline development, or evaluation frameworks rather than generic tasks. Your employer signs the form, then your DSO endorses it before USCIS approves the extension.
Can I start an AI ML internship on cap-gap if my H-1B is pending?
Cap-gap extends your OPT EAD automatically if you have an approved H-1B petition filed on your behalf before your OPT expires and the H-1B start date is October 1. Your work authorization continues through September 30 of the H-1B start year. You must remain in a valid OPT status, employed in a role tied to your STEM degree, and your employer must remain E-Verify enrolled throughout the cap-gap period.
Which STEM degrees make AI ML Intern roles eligible for the 24-month extension?
USCIS recognizes degrees in computer science, computer engineering, electrical engineering, statistics, applied mathematics, data science, and information technology as eligible for the STEM OPT extension when the role involves AI or ML work. Degrees in business analytics or information systems may qualify depending on their specific CIP code. Check the STEM Designated Degree Program List through USCIS and confirm your exact CIP code with your DSO before applying.