STEM OPT ML Software Engineer Jobs
ML Software Engineer roles sit squarely within STEM OPT eligibility, letting you work for up to 36 months total on your F-1 authorization. Your employer must be enrolled in E-Verify to hire you on the 24-month extension. A degree in computer science, electrical engineering, or a related STEM field qualifies.
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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 ML Software Engineer Jobs
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Get Access To All JobsTips for Finding STEM OPT Authorization as a ML Software Engineer
Verify your CIP code before applying
Your degree's Classification of Instructional Programs code must fall under an approved STEM field. Cross-check it against the DHS STEM Designated Degree Program List before you target roles, so you don't discover an eligibility gap after an offer.
Confirm E-Verify enrollment before accepting offers
Ask recruiters directly whether the company is enrolled in E-Verify, not just whether they 'sponsor' OPT. An employer can sponsor your initial OPT but still be ineligible for the 24-month STEM extension if they haven't completed E-Verify enrollment.
Use Migrate Mate to target verified STEM OPT employers
Search ML Software Engineer roles on Migrate Mate, which surfaces employers with confirmed E-Verify enrollment. This cuts the time you'd spend manually vetting companies and lets you focus applications on roles you're actually authorized to take.
Prepare your I-983 training plan before day one
Your employer must sign a Form I-983 outlining your training goals, duties, and learning objectives before your STEM OPT extension begins. Draft the ML-specific learning milestones in advance so the hiring manager isn't surprised by the paperwork requirement.
Target research-intensive ML roles for stronger I-983 alignment
Roles involving model development, research engineering, or applied ML research map more cleanly to the I-983's requirement that training relate directly to your STEM degree. Purely ops-focused or data-labeling roles can draw DSO scrutiny during reporting cycles.
File the STEM OPT extension at least 90 days early
USCIS recommends filing your I-765 extension application 90 days before your current EAD expires. ML hiring cycles can run long, so coordinating your offer timeline with your filing window prevents gaps in authorization between positions.
Frequently Asked Questions
Does my degree qualify me for the STEM OPT extension as an ML Software Engineer?
Your degree qualifies if it appears on the DHS STEM Designated Degree Program List, which covers fields like computer science, electrical engineering, mathematics, and statistics. Most ML Software Engineer roles require exactly these backgrounds. Confirm your specific Classification of Instructional Programs code with your DSO before filing, since the CIP code on your transcript determines eligibility, not just the degree name.
Does every employer hiring ML Software Engineers on STEM OPT need to be in E-Verify?
Yes, E-Verify enrollment is a hard requirement for the 24-month STEM OPT extension, not optional. Your employer must be enrolled before your extension is approved, and they must remain enrolled throughout your authorization period. If a company withdraws from E-Verify while you're employed, your STEM OPT authorization is at risk. Always verify enrollment status before accepting an offer. You can find ML Software Engineer roles from confirmed E-Verify employers on Migrate Mate.
What goes into the I-983 training plan for an ML Software Engineer role?
The I-983 requires your employer to describe the specific training you'll receive, how your duties relate to your STEM degree, and measurable learning objectives. For ML Software Engineer positions, this typically covers model architecture development, applied research methods, or ML systems engineering tied to your coursework. Both you and a company supervisor must sign it, and your DSO must receive it before your extension period begins.
Can I change ML Software Engineer jobs while on the STEM OPT extension?
Yes, you can change employers, but the new employer must also be enrolled in E-Verify, and you must report the change to your DSO within 10 days. A new I-983 training plan must be completed with the new employer before you start. Your existing EAD remains valid, but working for a non-E-Verify employer, even briefly, violates your status. Plan job transitions carefully around your authorization end date.
How does cap-gap protection work if I'm an ML Software Engineer with a pending H-1B?
If your employer files an H-1B visa petition on your behalf before your OPT or STEM OPT expires and you're selected in the lottery, cap-gap automatically extends your work authorization through September 30 of that fiscal year. This means you can continue working in your ML Software Engineer role without interruption while the H-1B is pending. USCIS governs cap-gap rules, and your DSO can issue an updated I-20 reflecting the extension.