Machine Learning Jobs at Intuit with Visa Sponsorship
Machine Learning jobs at Intuit span across financial technology products, including TurboTax, QuickBooks, and Credit Karma, where the company hires engineers and scientists. The company has a consistent track record of sponsoring work visas for ML roles and supports multiple visa pathways, making it a realistic target for international candidates.
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Come join the Fintech Risk AI/ML Smart Money Services (SMS) as a Senior Machine Learning Engineer. The SMS team is responsible for detecting and preventing fraud and financial risk for all Money Movement events at Intuit.
Responsibilities
As a Staff MLE, you will bridge the gap between advanced data science and scalable production engineering:
- Lead the conception, coding, and deployment of data science models at scale using the latest industry tools.
- Provide guidance and support leadership to business leaders and stakeholders on how best to harness available data for critical business needs.
- Help develop, maintain, and scale web services for the AI team which orchestrate various ML functions.
- Apply proven methods and hacking skills to work with divergent data types, data scales, and big data (petabytes).
- Partner closely with data scientists to understand, implement, and refine algorithms, building robust pipelines to train and deploy models.
- Discover, extract, and clean data from complex sources, making it machine learning-ready for large-scale analysis.
- Run regular A/B tests, gather data, draw conclusions on the impact of your models, and communicate results to peers, cross-functional partners, and leaders.
- Explore new technology shifts to determine how they might connect with customer benefits.
Qualifications
- BS, MS, or PhD degree in Computer Science, Statistics, Applied Mathematics, or a related field.
- 8+ years of experience developing predictive models, statistical analysis, or equivalent software engineering experience.
- Strong proficiency and experience with Object-Oriented Languages (OOD) such as Python, Scala, or Java.
- Deep knowledge of Data Science tools and frameworks (e.g., Python, Scikit, Pandas, TensorFlow, Keras, Spark).
- Strong software engineering fundamentals: data structures, algorithms, performance complexity, version control systems (Git), and the ability to write production-ready code.
- Demonstrated experience with web services (e.g., REST) and API design.
- Experience integrating applications and platforms with cloud technologies (e.g., AWS) and deploying highly scalable software supporting millions or more users.
- Practical experience with advanced concepts such as Supervised and Unsupervised ML techniques, Generative AI (autoencoders, GANs, VAEs), and GPU acceleration (CUDA and cuDNN).
- Excellent communication skills, including the ability to conduct meetings, make professional presentations, and explain complex technical concepts to non-technical business stakeholders.
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs. Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.
The expected base pay range for this position is:
- Mountain View $202,500 - $274,000
Overview
Come join the Fintech Risk AI/ML Smart Money Services (SMS) as a Senior Machine Learning Engineer. The SMS team is responsible for detecting and preventing fraud and financial risk for all Money Movement events at Intuit.
Responsibilities
As a Staff MLE, you will bridge the gap between advanced data science and scalable production engineering:
- Lead the conception, coding, and deployment of data science models at scale using the latest industry tools.
- Provide guidance and support leadership to business leaders and stakeholders on how best to harness available data for critical business needs.
- Help develop, maintain, and scale web services for the AI team which orchestrate various ML functions.
- Apply proven methods and hacking skills to work with divergent data types, data scales, and big data (petabytes).
- Partner closely with data scientists to understand, implement, and refine algorithms, building robust pipelines to train and deploy models.
- Discover, extract, and clean data from complex sources, making it machine learning-ready for large-scale analysis.
- Run regular A/B tests, gather data, draw conclusions on the impact of your models, and communicate results to peers, cross-functional partners, and leaders.
- Explore new technology shifts to determine how they might connect with customer benefits.
Qualifications
- BS, MS, or PhD degree in Computer Science, Statistics, Applied Mathematics, or a related field.
- 8+ years of experience developing predictive models, statistical analysis, or equivalent software engineering experience.
- Strong proficiency and experience with Object-Oriented Languages (OOD) such as Python, Scala, or Java.
- Deep knowledge of Data Science tools and frameworks (e.g., Python, Scikit, Pandas, TensorFlow, Keras, Spark).
- Strong software engineering fundamentals: data structures, algorithms, performance complexity, version control systems (Git), and the ability to write production-ready code.
- Demonstrated experience with web services (e.g., REST) and API design.
- Experience integrating applications and platforms with cloud technologies (e.g., AWS) and deploying highly scalable software supporting millions or more users.
- Practical experience with advanced concepts such as Supervised and Unsupervised ML techniques, Generative AI (autoencoders, GANs, VAEs), and GPU acceleration (CUDA and cuDNN).
- Excellent communication skills, including the ability to conduct meetings, make professional presentations, and explain complex technical concepts to non-technical business stakeholders.
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs. Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.
The expected base pay range for this position is:
- Mountain View $202,500 - $274,000
See all 52+ Machine Learning Jobs at Intuit
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Jobs at Intuit.
Get Access To All JobsTips for Finding Machine Learning Jobs at Intuit
Align your ML portfolio to Intuit's products
Intuit's ML teams work on financial forecasting, natural language processing for tax guidance, and fraud detection. Frame your portfolio projects around these domains before applying. A generic computer vision project is less compelling than demonstrated experience with structured financial data.
Clarify your visa type before the recruiter screen
Intuit sponsors several visa categories, but each has different timelines and filing requirements. Tell the recruiter your current status, your authorization expiration date, and whether you're cap-subject before the first technical screen to avoid late-stage mismatches.
Time your application around the H-1B cap cycle
If you need H-1B sponsorship, USCIS opens registration in March for an October 1 start. Plan your Intuit application so an offer can realistically land in February or early March, giving the legal team enough runway to register you in that lottery cycle.
Use OPT STEM extension strategically at Intuit
F-1 graduates in ML qualify for the 24-month STEM OPT extension, which gives you up to three years of work authorization. Confirm with HR that Intuit is enrolled in E-Verify, a requirement for STEM OPT, before you rely on this timeline in your planning.
Prepare for a multi-round technical process
Intuit's ML interviews typically include a coding screen, an ML system design round, and a domain-specific case. Having your Green Card or visa timeline documented clearly lets you negotiate start dates confidently after clearing all rounds without scrambling for authorization details.
Find open ML roles at Intuit through Migrate Mate
Searching for visa-friendly ML openings manually is slow. Use Migrate Mate to filter Intuit's current Machine Learning roles by visa type, so you're only reviewing positions where your sponsorship category is already confirmed as supported.
Frequently Asked Questions
Does Intuit sponsor H-1B visas for Machine Learning roles?
Yes, Intuit sponsors H-1B visas for Machine Learning positions. The company files petitions through the standard USCIS cap process, with registration typically opening in March for an October 1 start date. If you're currently on F-1 OPT, coordinating your offer timeline around the H-1B lottery cycle is critical to avoid a gap in work authorization.
How do I apply for Machine Learning jobs at Intuit?
Start by identifying open ML roles that align with your specialization, whether that's NLP, recommendation systems, or financial forecasting. Apply through Intuit's careers portal and be upfront about your visa status in early recruiter conversations. You can browse current visa-sponsored openings filtered by role and visa type on Migrate Mate before submitting a formal application.
Which visa types does Intuit commonly use for Machine Learning hires?
Intuit sponsors a range of visa categories for ML roles, including H-1B, E-3 visa for Australian citizens, TN visa for Canadian and Mexican nationals, F-1 OPT and CPT for students, J-1 visa for exchange visitors, and employment-based Green Cards through the EB-2 and EB-3 pathways. The right category depends on your nationality, education level, and current immigration status.
What qualifications does Intuit expect for sponsored Machine Learning roles?
Most ML positions at Intuit require a bachelor's degree at minimum in computer science, statistics, or a related quantitative field, with a master's or PhD common for senior and research-oriented roles. Hands-on experience with large-scale data pipelines, model deployment, and frameworks such as TensorFlow or PyTorch is expected. Domain knowledge in fintech, NLP, or fraud detection strengthens your candidacy significantly.
How long does the visa sponsorship process take after receiving an Intuit offer?
Timeline depends on your visa category. H-1B petitions filed under standard processing take three to six months after USCIS receives the petition, while premium processing reduces that to 15 business days. E-3 and TN visas can often be obtained within a few weeks of receiving the offer letter and supporting documents. PERM-based Green Card sponsorship, if initiated, typically takes one to two years before a petition is filed.