Artificial Intelligence Scientist Jobs at Intuit with Visa Sponsorship
Artificial Intelligence Scientist jobs at Intuit involve building intelligent financial tools used by millions of people, and the company has a well-established track record of sponsoring work visas across this function. If you're an international candidate targeting AI roles in the fintech space, Intuit is a serious option.
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Intuit’s Consumer Group, including TurboTax and Credit Karma, empowers millions of individuals to take control of their finances. By harnessing the power of data and artificial intelligence (AI), we continuously innovate across consumer lending, banking, and money-movement products to deliver greater value and to protect our members and our platform from risk.
As we expand our Consumer Risk AI Science charter, Intuit Credit Karma is looking for an experienced, hands-on player-coach to join us as a Sr Staff, AI Science. In this role you will build, deploy, and monitor credit risk and fraud risk AI/ML models that directly affect hundreds of thousands of customers — while staying close enough to the technical work to set a high bar, unblock the team, and personally drive the most complex, ambiguous modeling problems. You will own credit risk modeling for our consumer lending and fast-money products, and you will lead the expansion of our fraud modeling program — across three business verticals: Banking, Workforce Wallet (WFS), and CK Invest. You will partner with the broader Consumer Risk leadership team to set strategy, drive delivery, and develop talent.
Responsibilities
Team & Delivery Leadership
- Lead, and build AI/ML models
- Set the modeling strategy — owning accountability for the design, development, deployment, and monitoring of credit risk and fraud risk models; set technical direction, review the team’s work, remove blockers, and share ownership of program-level success and key results.
- Direct the team’s data strategy — governing the sourcing and use of internal and third-party data such as credit bureau (Experian, TransUnion, Lexis Nexis), cashflow transaction (Plaid, Nova Credit), identity and fraud (Socure, Emailage, ID Analytics) and Intuit tax data — to build proprietary risk attributes and models.
- Own credit risk AI science for the consumer lending and fast-money portfolio — including first-generation and next-generation credit risk underwriting, cashflow-based underwriting, behavioral, and targeting / eligibility models — for short-term lending products (e.g., tax refund advances, BNPL, installment loans, line of credit, and early wage access).
- Lead fraud AI/ML modeling across three verticals — Banking, Workforce Wallet (WFS), and CK Invest — owning the fraud model roadmap and its integration into real-time and batch decisioning across the full fraud lifecycle: onboarding, money-in, money-out and account takeover (ATO) fraud.
- Own the end-to-end model lifecycle — across cloud infrastructure on Intuit AWS (SageMaker, Redshift, Databricks) and CK GCP Vertex AI
- Own model governance and regulatory compliance (SR 11-7, FCRA, ECOA), including fair lending reviews, adverse action reason codes, and periodic performance reporting to partner banks and internal governance.
- Partner with Credit and Fraud Policy, Product, Engineering, Legal & Compliance, Model Validation, and partner banks (WebBank, MVB) to embed models into decisioning and to shape risk solutions at the earliest stages of every product launch.
- Communicate team progress, model impact, and roadmap to senior Risk and Business leadership through regular updates, deep dives, and executive reviews.
- Lead hiring for the AI Science organization — conducting interviews, representing the modeling function on cross-team panels, and onboarding new employees — and sponsor knowledge-sharing sessions and adoption of modern AI tooling to increase team velocity and productivity.
- Champion a culture of Agentic AI adoption while guiding the team to design, build, and deploy AI agents and orchestration workflows that automate the end-to-end model development lifecycle—data exploration, feature engineering, validation, training, evaluation, and monitoring—to accelerate team velocity and productivity.
Qualifications
Minimum Requirements
- Advanced degree (Ph.D. / MS) in Computer Science, Data Science, AI, Mathematics, Statistics, Econometrics, Physics, or a related quantitative discipline (or equivalent experience).
- 8+ years of experience in AI Science / Machine Learning, successfully delivering data-driven products.
- Authoritative knowledge of Python and SQL.
- Relevant fintech experience in credit risk and/or fraud risk modeling, with a deep understanding of payment systems, money movement, banking, and lending.
- Hands-on expertise developing, deploying, monitoring and maintaining a variety of machine learning techniques, including but not limited to, deep learning (transformers, sequence modeling), tree-based models, reinforcement learning, clustering, time series, causal analysis, and natural language processing.
- Experience leveraging credit bureau, tax, cashflow, identity, and device/behavioral data in risk model development.
- Deep understanding of credit risk concepts (PD calibration, reject inference, adverse action logic, risk segmentation) and/or fraud typologies (onboarding/synthetic ID, ACH/deposit fraud, transaction / debit auth fraud, ATO, fraud rings).
- Expertise designing efficient, reusable data pipelines and frameworks for ML models.
- Strong business problem-solving, communication, collaboration, and people-leadership skills; able to communicate a vision and inspire others to innovate.
Preferred Qualifications
- Proficiency in deep learning frameworks such as TensorFlow or PyTorch.
- Experience with public cloud platforms (GCP or AWS) and workflow orchestration tools such as Apache Airflow.
- Strong background in MLOps infrastructure and tooling — particularly Vertex AI or AWS SageMaker — including pipelines, automated retraining, monitoring, and version control.
- Experience with real-time / streaming model deployment and feature stores for low-latency fraud decisioning.
- Working knowledge of LLMs and AI agents (prompt engineering, RAG, tool calling, agentic workflows) and Gen AI orchestration frameworks (e.g., LangChain, LangGraph).
- Experience with model governance and regulatory frameworks (SR 11-7, FCRA, ECOA) and fair lending / fair banking review.
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 $226,000 - $306,000
Overview
Intuit’s Consumer Group, including TurboTax and Credit Karma, empowers millions of individuals to take control of their finances. By harnessing the power of data and artificial intelligence (AI), we continuously innovate across consumer lending, banking, and money-movement products to deliver greater value and to protect our members and our platform from risk.
As we expand our Consumer Risk AI Science charter, Intuit Credit Karma is looking for an experienced, hands-on player-coach to join us as a Sr Staff, AI Science. In this role you will build, deploy, and monitor credit risk and fraud risk AI/ML models that directly affect hundreds of thousands of customers — while staying close enough to the technical work to set a high bar, unblock the team, and personally drive the most complex, ambiguous modeling problems. You will own credit risk modeling for our consumer lending and fast-money products, and you will lead the expansion of our fraud modeling program — across three business verticals: Banking, Workforce Wallet (WFS), and CK Invest. You will partner with the broader Consumer Risk leadership team to set strategy, drive delivery, and develop talent.
Responsibilities
Team & Delivery Leadership
- Lead, and build AI/ML models
- Set the modeling strategy — owning accountability for the design, development, deployment, and monitoring of credit risk and fraud risk models; set technical direction, review the team’s work, remove blockers, and share ownership of program-level success and key results.
- Direct the team’s data strategy — governing the sourcing and use of internal and third-party data such as credit bureau (Experian, TransUnion, Lexis Nexis), cashflow transaction (Plaid, Nova Credit), identity and fraud (Socure, Emailage, ID Analytics) and Intuit tax data — to build proprietary risk attributes and models.
- Own credit risk AI science for the consumer lending and fast-money portfolio — including first-generation and next-generation credit risk underwriting, cashflow-based underwriting, behavioral, and targeting / eligibility models — for short-term lending products (e.g., tax refund advances, BNPL, installment loans, line of credit, and early wage access).
- Lead fraud AI/ML modeling across three verticals — Banking, Workforce Wallet (WFS), and CK Invest — owning the fraud model roadmap and its integration into real-time and batch decisioning across the full fraud lifecycle: onboarding, money-in, money-out and account takeover (ATO) fraud.
- Own the end-to-end model lifecycle — across cloud infrastructure on Intuit AWS (SageMaker, Redshift, Databricks) and CK GCP Vertex AI
- Own model governance and regulatory compliance (SR 11-7, FCRA, ECOA), including fair lending reviews, adverse action reason codes, and periodic performance reporting to partner banks and internal governance.
- Partner with Credit and Fraud Policy, Product, Engineering, Legal & Compliance, Model Validation, and partner banks (WebBank, MVB) to embed models into decisioning and to shape risk solutions at the earliest stages of every product launch.
- Communicate team progress, model impact, and roadmap to senior Risk and Business leadership through regular updates, deep dives, and executive reviews.
- Lead hiring for the AI Science organization — conducting interviews, representing the modeling function on cross-team panels, and onboarding new employees — and sponsor knowledge-sharing sessions and adoption of modern AI tooling to increase team velocity and productivity.
- Champion a culture of Agentic AI adoption while guiding the team to design, build, and deploy AI agents and orchestration workflows that automate the end-to-end model development lifecycle—data exploration, feature engineering, validation, training, evaluation, and monitoring—to accelerate team velocity and productivity.
Qualifications
Minimum Requirements
- Advanced degree (Ph.D. / MS) in Computer Science, Data Science, AI, Mathematics, Statistics, Econometrics, Physics, or a related quantitative discipline (or equivalent experience).
- 8+ years of experience in AI Science / Machine Learning, successfully delivering data-driven products.
- Authoritative knowledge of Python and SQL.
- Relevant fintech experience in credit risk and/or fraud risk modeling, with a deep understanding of payment systems, money movement, banking, and lending.
- Hands-on expertise developing, deploying, monitoring and maintaining a variety of machine learning techniques, including but not limited to, deep learning (transformers, sequence modeling), tree-based models, reinforcement learning, clustering, time series, causal analysis, and natural language processing.
- Experience leveraging credit bureau, tax, cashflow, identity, and device/behavioral data in risk model development.
- Deep understanding of credit risk concepts (PD calibration, reject inference, adverse action logic, risk segmentation) and/or fraud typologies (onboarding/synthetic ID, ACH/deposit fraud, transaction / debit auth fraud, ATO, fraud rings).
- Expertise designing efficient, reusable data pipelines and frameworks for ML models.
- Strong business problem-solving, communication, collaboration, and people-leadership skills; able to communicate a vision and inspire others to innovate.
Preferred Qualifications
- Proficiency in deep learning frameworks such as TensorFlow or PyTorch.
- Experience with public cloud platforms (GCP or AWS) and workflow orchestration tools such as Apache Airflow.
- Strong background in MLOps infrastructure and tooling — particularly Vertex AI or AWS SageMaker — including pipelines, automated retraining, monitoring, and version control.
- Experience with real-time / streaming model deployment and feature stores for low-latency fraud decisioning.
- Working knowledge of LLMs and AI agents (prompt engineering, RAG, tool calling, agentic workflows) and Gen AI orchestration frameworks (e.g., LangChain, LangGraph).
- Experience with model governance and regulatory frameworks (SR 11-7, FCRA, ECOA) and fair lending / fair banking review.
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 $226,000 - $306,000
See all 59+ Artificial Intelligence Scientist Jobs at Intuit
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Artificial Intelligence Scientist Jobs at Intuit.
Get Access To All JobsTips for Finding Artificial Intelligence Scientist Jobs at Intuit
Align your research background to financial AI
Intuit's AI work centers on tax automation, natural language processing for financial documents, and personalized money insights. Frame your CV around applied ML systems that affect real users at scale, not pure research publications.
Prepare your credential documentation early
For H-1B and E-3 petitions, USCIS requires evidence that your degree directly supports the role. Get your transcripts evaluated by a NACES-accredited service before you receive an offer, so you're not scrambling after signing.
Clarify your visa type during the offer stage
Intuit sponsors multiple visa categories, and which one applies to you affects your timeline. Australian citizens should specifically ask about E-3 eligibility during offer negotiation, since it processes faster and doesn't depend on the H-1B lottery.
Use Migrate Mate to target Intuit AI openings
Artificial Intelligence Scientist roles at Intuit open and close quickly. Use Migrate Mate to filter specifically for Intuit positions that include visa sponsorship, so you're applying to active roles rather than chasing outdated listings.
Understand OPT cap-gap before your start date
If you're transitioning from F-1 OPT and your H-1B is filed before the April 1 deadline, cap-gap protection keeps you authorized through October 1. Confirm your OPT expiration date with your DSO before accepting a summer start date.
Verify your I-140 strategy for long-term sponsorship
For candidates from India or China, Intuit's willingness to file an EB-2 or EB-3 I-140 early matters significantly given green card backlogs. Raise green card sponsorship in the offer negotiation, not after you've already started.
Frequently Asked Questions
Does Intuit sponsor H-1B visas for Artificial Intelligence Scientists?
Yes, Intuit sponsors H-1B visas for Artificial Intelligence Scientists. The company has a consistent track record of filing H-1B petitions for technical roles, including those in machine learning and AI research. Because H-1B sponsorship depends on the annual lottery, timing your application cycle and having your documents in order before the March registration window matters.
Which visa types are commonly used for Artificial Intelligence Scientist roles at Intuit?
Intuit sponsors H-1B, E-3 visa, TN visa, F-1 OPT, F-1 CPT, J-1 visa, and employment-based Green Cards including EB-2 and EB-3 for this role. Australian citizens are well-positioned to pursue the E-3 visa, which has no lottery and processes at the consulate. Canadian and Mexican citizens may qualify for TN visa status under the USMCA, which is employer-filed and faster than H-1B.
How do I apply for Artificial Intelligence Scientist jobs at Intuit?
You can browse and apply for Artificial Intelligence Scientist roles at Intuit through Migrate Mate, which filters specifically for positions open to international candidates requiring visa sponsorship. When applying, tailor your application to highlight experience with production ML systems, NLP, or AI applied to financial data, since those map directly to Intuit's core product areas.
What qualifications does Intuit typically expect for Artificial Intelligence Scientist roles?
Intuit generally expects a master's or Ph.D. in computer science, machine learning, statistics, or a closely related field for Artificial Intelligence Scientist positions. Hands-on experience building and deploying ML models at scale, familiarity with large language models or NLP pipelines, and the ability to translate research into product-facing features are all strong signals for this role.
How do I plan my timeline around visa sponsorship when targeting Intuit?
If you need H-1B sponsorship, Intuit must file your petition in April for an October 1 start date, so receiving an offer by late February or early March is critical. For E-3 or TN candidates, consular processing typically runs two to four weeks, giving more scheduling flexibility. OPT candidates should confirm their authorization end date with their DSO before committing to a start date.