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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Intuit Credit Karma is looking for a results-oriented and skilled Senior Machine Learning Engineer to join our team, focusing on building and deploying the infrastructure, services, and SDKs enabling Credit Karma’s Data Science teams to prototype, deploy, score, and monitor predictive models at scale. The ideal candidate will have expertise in MLOps, big data technologies, software development, data engineering, deep learning ML frameworks, and is driven to stay current with the fast moving ML & AI landscape and integrate innovations into our platforms.
Responsibilities
- Training Platform: Design, build, and maintain our Next Generation federated ML Platform - built on Vertex AI and Kubernetes. Contribute to our python SDK, which enables Data Scientists to efficiently develop, define, and deploy no-human-in-the-loop auto-refreshing deep learning and tree-based ML Models.
- ML Features Platform: Design, build, and maintain our feature engineering and feature stores services supporting batch and streaming features - built on Vertex featurestore, Chronon, Databricks Tecton.
- Training Data: Design and build out capabilities supporting training data pipelines and centralized modeling training datasets. Integrate labelbox, snorkel, and Intuit’s GenAI and human-backed AI labeling platform.
- Technical Support & Collaboration: Provide technical support for owned products, including performing on-call duties, resolving production site issues, and improving the performance and scalability of services. Collaborate with cross-functional stakeholders to identify high-impact opportunities, translate business and analytical requirements, develop project plans, and report business value.
- Production Deployment and Monitoring: Platform-level monitoring for features, training data, training, and offline batch scoring. Provide utilities and capabilities to enable Data Scientists to do pipeline-level monitoring for training and scoring.
- Innovation & Mentorship: Stay current on innovation trends and propose solutions that integrate those back into our platform. Support & mentor other members of our team on current trends, best practices, and their projects.
Qualifications
- MS in Computer Science, Mathematics, Statistics, Machine Learning, or a related quantitative discipline
- 7+ years of industry experience in Machine Learning, Data Science and related areas, ideally in hyper-growth consumer Internet scenarios
- Deep understanding and ability to architect and develop next-generation ML systems, staying ahead of industry trends and integrating latest advancements (e.g. GenAI)
- Strong background in programming languages (e.g., Python, Java, SQL)
- Experience with deep learning frameworks (e.g., Tensorflow, PyTorch)
Preferred qualifications
- MLOps & Infrastructure: Experience with managing a large-scale platform that services many hundreds of auto-refreshing machine learning models deploying into production with no human-in-the-loop.
- Communication: Exceptional ability to communicate technical concepts to non-technical stakeholders and drive organizational alignment.
- Distributed Processing: Experience with high-volume data processing and frameworks like Spark, Dataflow, Dask, Ray.
- Deep Learning: Extensive Experience with deep learning frameworks such as Tensorflow or PyTorch.
- Google Cloud: Experience with managing platforms backed by Google Cloud ML and AI services.
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will 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: Bay Area: $202,500-274,000; Oakland: $171,000 - $231,500.
Overview
Intuit Credit Karma is looking for a results-oriented and skilled Senior Machine Learning Engineer to join our team, focusing on building and deploying the infrastructure, services, and SDKs enabling Credit Karma’s Data Science teams to prototype, deploy, score, and monitor predictive models at scale. The ideal candidate will have expertise in MLOps, big data technologies, software development, data engineering, deep learning ML frameworks, and is driven to stay current with the fast moving ML & AI landscape and integrate innovations into our platforms.
Responsibilities
- Training Platform: Design, build, and maintain our Next Generation federated ML Platform - built on Vertex AI and Kubernetes. Contribute to our python SDK, which enables Data Scientists to efficiently develop, define, and deploy no-human-in-the-loop auto-refreshing deep learning and tree-based ML Models.
- ML Features Platform: Design, build, and maintain our feature engineering and feature stores services supporting batch and streaming features - built on Vertex featurestore, Chronon, Databricks Tecton.
- Training Data: Design and build out capabilities supporting training data pipelines and centralized modeling training datasets. Integrate labelbox, snorkel, and Intuit’s GenAI and human-backed AI labeling platform.
- Technical Support & Collaboration: Provide technical support for owned products, including performing on-call duties, resolving production site issues, and improving the performance and scalability of services. Collaborate with cross-functional stakeholders to identify high-impact opportunities, translate business and analytical requirements, develop project plans, and report business value.
- Production Deployment and Monitoring: Platform-level monitoring for features, training data, training, and offline batch scoring. Provide utilities and capabilities to enable Data Scientists to do pipeline-level monitoring for training and scoring.
- Innovation & Mentorship: Stay current on innovation trends and propose solutions that integrate those back into our platform. Support & mentor other members of our team on current trends, best practices, and their projects.
Qualifications
- MS in Computer Science, Mathematics, Statistics, Machine Learning, or a related quantitative discipline
- 7+ years of industry experience in Machine Learning, Data Science and related areas, ideally in hyper-growth consumer Internet scenarios
- Deep understanding and ability to architect and develop next-generation ML systems, staying ahead of industry trends and integrating latest advancements (e.g. GenAI)
- Strong background in programming languages (e.g., Python, Java, SQL)
- Experience with deep learning frameworks (e.g., Tensorflow, PyTorch)
Preferred qualifications
- MLOps & Infrastructure: Experience with managing a large-scale platform that services many hundreds of auto-refreshing machine learning models deploying into production with no human-in-the-loop.
- Communication: Exceptional ability to communicate technical concepts to non-technical stakeholders and drive organizational alignment.
- Distributed Processing: Experience with high-volume data processing and frameworks like Spark, Dataflow, Dask, Ray.
- Deep Learning: Extensive Experience with deep learning frameworks such as Tensorflow or PyTorch.
- Google Cloud: Experience with managing platforms backed by Google Cloud ML and AI services.
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will 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: Bay Area: $202,500-274,000; Oakland: $171,000 - $231,500.
Tips 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.