Machine Learning Jobs at JPMorganChase with Visa Sponsorship
Machine Learning jobs at JPMorganChase involve building systems across risk modeling, fraud detection, trading infrastructure, and consumer products, with the firm maintaining a consistent track record of sponsoring work visas for qualified ML engineers and researchers. If you're targeting a role here, you're looking at one of the most active financial services sponsors in this space.
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We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. As an Applied Machine Learning Scientist within our dynamic team, you will lead the development of scalable, production-grade advanced ML solutions across natural language processing, speech recognition, recommendation systems, information retrieval, and agentic AI. You will play a key role in delivering Generative AI capabilities – designing and productionizing LLM-powered systems such as RAG (Retrieval Augmented Generation), tool/function-calling agents, and structured generation to automate complex workflows and improve customer experiences. You will collaborate with product, engineering, and control partners to translate ambiguous problems into measurable goals, deliver robust models, and operate them reliably in production. You bring strong deep learning and transformer-based modeling expertise, as well as hands-on experience in fine-tuning and evaluation. You must have a strong passion for machine learning, strong analytical thinking, a deep desire to learn, and high motivation. You must also invest independent time in learning, researching, and experimenting with new innovations, and contribute to a strong knowledge-sharing culture.
Job Responsibilities
- Lead and deploy state-of-the-art advanced machine learning systems across NLP, speech recognition, recommendation systems, and information retrieval.
- Design and build agentic AI systems for multi-step workflows, including tool/function calling, multi-agent orchestration, planning, grounding, and safety guardrails.
- Use reinforcement learning (policy optimization, bandits, RLHF-style approaches where appropriate) to improve personalization, dialog policies, and sequential decision-making systems.
- Fine-tune and adapt LLMs/SLMs using PEFT (LoRA, AdaLoRA, IA3), distillation, and quantization; optimize for quality, latency, cost, and production constraints.
- Select and innovate on ML strategies for various banking problems.
- Analyze and evaluate the ongoing performance of developed ML systems.
- Collaborate with multiple partner teams, such as Business, Technology, Product Management, Design, Analytics, and Model Governance to deploy solutions into production.
- Build domain understanding to identify high-impact opportunities, ensure responsible AI usage, and drive measurable outcomes (customer experience, automation, accuracy, and efficiency).
- Implement privacy, safety, and security controls for GenAI systems, including PCI handling/redaction, policy checks, jailbreak resistance, and auditability.
Required Qualifications, Capabilities, And Skills
- MS with 7+ years, or PhD with 4+ years of hands-on industry experience in building and deploying machine learning systems (NLP/Information Retrieval/Recommendation System and/or GenAI) in production environment
- Good understanding of the latest advancement of NLP concepts, such as the transformer architecture, knowledge distillation, transfer learning, and representation learning.
- Applied GenAI experience with LLMs and the ability to fine-tune and deploy SLMs for targeted use cases, familiarity with prompt design, grounded generation, and RAG.
- Experience with scaling LLM systems (caching, batching, prompt/version governance, evaluation harnesses)
- Strong foundation in machine learning, deep learning, and statistical modelling, including model evaluation and error analysis.
- Solid understanding of Information Retrieval concepts (indexing, ranking, dense/sparse retrieval, re-ranking) and/or recommendation systems.
- Ability to design experiments — establish strong baselines, choose meaningful metrics, and evaluate model performance rigorously
- Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
- Proficiency in Python and common ML libraries (PyTorch/TensorFlow, Hugging Face, scikit-learn), and ability to write production-quality code.
- Ability to collaborate in cross-functional environments with product, engineering, and control partners.
- Solid written and spoken communication skills
Preferred Qualifications, Capabilities, And Skills
- 5 years of hands-on experience with virtual assistant model development and optimization
- Experience orchestrating multi-agent teams with supervisor agents, debate/consensus mechanisms, and role-specialized toolkits for complex enterprise tasks.
- Building agent governance and eval suites: red-teaming, adversarial tests, safety scorecards, regression suites for prompts/tools
- Experience with RL/bandits, preference optimization, or human feedback loops for personalization.
- Experience in regulated finance domains and working with risk/control processes.
- Experience with MLOps/LLMOps: CI/CD for models, monitoring/alerting, model versioning, evaluation of pipelines, and rollback strategies.
- Experience with A/B experimentation and data/metric-driven product development.
This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChase's review of criminal conviction history, including pretrial diversions or program entries.
About us
Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. Equal Opportunity Employer/Disability/Veterans
About The Team
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction. The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.
Job Description
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. As an Applied Machine Learning Scientist within our dynamic team, you will lead the development of scalable, production-grade advanced ML solutions across natural language processing, speech recognition, recommendation systems, information retrieval, and agentic AI. You will play a key role in delivering Generative AI capabilities – designing and productionizing LLM-powered systems such as RAG (Retrieval Augmented Generation), tool/function-calling agents, and structured generation to automate complex workflows and improve customer experiences. You will collaborate with product, engineering, and control partners to translate ambiguous problems into measurable goals, deliver robust models, and operate them reliably in production. You bring strong deep learning and transformer-based modeling expertise, as well as hands-on experience in fine-tuning and evaluation. You must have a strong passion for machine learning, strong analytical thinking, a deep desire to learn, and high motivation. You must also invest independent time in learning, researching, and experimenting with new innovations, and contribute to a strong knowledge-sharing culture.
Job Responsibilities
- Lead and deploy state-of-the-art advanced machine learning systems across NLP, speech recognition, recommendation systems, and information retrieval.
- Design and build agentic AI systems for multi-step workflows, including tool/function calling, multi-agent orchestration, planning, grounding, and safety guardrails.
- Use reinforcement learning (policy optimization, bandits, RLHF-style approaches where appropriate) to improve personalization, dialog policies, and sequential decision-making systems.
- Fine-tune and adapt LLMs/SLMs using PEFT (LoRA, AdaLoRA, IA3), distillation, and quantization; optimize for quality, latency, cost, and production constraints.
- Select and innovate on ML strategies for various banking problems.
- Analyze and evaluate the ongoing performance of developed ML systems.
- Collaborate with multiple partner teams, such as Business, Technology, Product Management, Design, Analytics, and Model Governance to deploy solutions into production.
- Build domain understanding to identify high-impact opportunities, ensure responsible AI usage, and drive measurable outcomes (customer experience, automation, accuracy, and efficiency).
- Implement privacy, safety, and security controls for GenAI systems, including PCI handling/redaction, policy checks, jailbreak resistance, and auditability.
Required Qualifications, Capabilities, And Skills
- MS with 7+ years, or PhD with 4+ years of hands-on industry experience in building and deploying machine learning systems (NLP/Information Retrieval/Recommendation System and/or GenAI) in production environment
- Good understanding of the latest advancement of NLP concepts, such as the transformer architecture, knowledge distillation, transfer learning, and representation learning.
- Applied GenAI experience with LLMs and the ability to fine-tune and deploy SLMs for targeted use cases, familiarity with prompt design, grounded generation, and RAG.
- Experience with scaling LLM systems (caching, batching, prompt/version governance, evaluation harnesses)
- Strong foundation in machine learning, deep learning, and statistical modelling, including model evaluation and error analysis.
- Solid understanding of Information Retrieval concepts (indexing, ranking, dense/sparse retrieval, re-ranking) and/or recommendation systems.
- Ability to design experiments — establish strong baselines, choose meaningful metrics, and evaluate model performance rigorously
- Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
- Proficiency in Python and common ML libraries (PyTorch/TensorFlow, Hugging Face, scikit-learn), and ability to write production-quality code.
- Ability to collaborate in cross-functional environments with product, engineering, and control partners.
- Solid written and spoken communication skills
Preferred Qualifications, Capabilities, And Skills
- 5 years of hands-on experience with virtual assistant model development and optimization
- Experience orchestrating multi-agent teams with supervisor agents, debate/consensus mechanisms, and role-specialized toolkits for complex enterprise tasks.
- Building agent governance and eval suites: red-teaming, adversarial tests, safety scorecards, regression suites for prompts/tools
- Experience with RL/bandits, preference optimization, or human feedback loops for personalization.
- Experience in regulated finance domains and working with risk/control processes.
- Experience with MLOps/LLMOps: CI/CD for models, monitoring/alerting, model versioning, evaluation of pipelines, and rollback strategies.
- Experience with A/B experimentation and data/metric-driven product development.
This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChase's review of criminal conviction history, including pretrial diversions or program entries.
About us
Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. Equal Opportunity Employer/Disability/Veterans
About The Team
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction. The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.
See all 38+ Machine Learning Jobs at JPMorganChase
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Jobs at JPMorganChase.
Get Access To All JobsTips for Finding Machine Learning Jobs at JPMorganChase
Align your ML portfolio to financial risk use cases
JPMorganChase's ML hiring clusters around credit risk models, fraud detection, and algorithmic trading. Framing your portfolio projects around time-series forecasting, anomaly detection, or NLP on financial documents directly maps to what their teams are building.
Confirm your visa type before applying
JPMorganChase sponsors H-1B, E-3, and H-1B1 visas. Australians on the E-3 and Singaporeans or Chileans on the H-1B1 face a much smoother path than cap-subject H-1B applicants, so clarifying your eligibility before outreach prevents wasted effort on both sides.
Target teams with established PERM infrastructure
In financial services firms this size, ML roles within the commercial banking and consumer technology divisions have historically run PERM-based Green Card sponsorship. Asking recruiters whether a specific team has a track record of PERM filings is a legitimate and practical screening question.
Find open ML roles at JPMorganChase using Migrate Mate
Search for JPMorganChase ML positions on Migrate Mate to filter specifically for roles tied to visa sponsorship. This saves time you'd otherwise spend manually screening job listings with no sponsorship signal.
Time your H-1B application to the April cap season
If you need a cap-subject H-1B, your start date will be October 1 at the earliest. Factor this into your offer negotiation, since large financial institutions like JPMorganChase are familiar with this cycle and routinely structure start dates and onboarding around it.
Get your credentials evaluated before the offer stage
JPMorganChase's ML roles often require a master's or doctorate in a quantitative field. If your degree is from outside the U.S., a credential evaluation from a NACES-member organization confirms equivalency to USCIS standards before the petition is filed, avoiding delays after the offer.
Frequently Asked Questions
Does JPMorganChase sponsor H-1B visas for Machine Learning roles?
Yes, JPMorganChase sponsors H-1B visas for machine learning positions. As a large financial services employer, the firm has the legal and HR infrastructure to handle H-1B petitions, including premium processing where needed. If you're subject to the H-1B cap, petitions are filed in April for an October 1 start date, so plan your job search timeline accordingly.
Which visa types does JPMorganChase sponsor for Machine Learning positions?
JPMorganChase sponsors H-1B, H-1B1 visa, and E-3 visas for machine learning roles, and supports employment-based Green Card sponsorship through the EB-2 and EB-3 categories via the PERM labor certification process. Australians can use the E-3 visa, which has no lottery. Singaporean and Chilean nationals may qualify for the H-1B1, which is also cap-exempt and processed outside the annual lottery.
What qualifications does JPMorganChase expect for Machine Learning roles?
Most machine learning positions at JPMorganChase require a master's or doctoral degree in computer science, statistics, applied mathematics, or a related quantitative field, along with hands-on experience in Python, PyTorch or TensorFlow, and large-scale data pipelines. Roles in trading or risk typically expect familiarity with financial time-series data, while consumer-facing ML teams often prioritize NLP and recommendation systems experience.
How do I apply for Machine Learning jobs at JPMorganChase?
Browse current machine learning openings at JPMorganChase on Migrate Mate, where listings are filtered for visa sponsorship eligibility. Apply directly through JPMorganChase's careers portal and tailor your resume to the specific team's domain. For ML roles, technical screens typically include a coding assessment followed by system design and ML fundamentals interviews before reaching the offer stage.
How do I understand the sponsorship timeline for a Machine Learning role at JPMorganChase?
Timeline depends on your visa type. E-3 and H-1B1 visa applicants can often begin work within four to eight weeks of an offer, since those visas are processed at U.S. consulates without a cap. Cap-subject H-1B applicants must wait for the April registration window and an October 1 start date. For Green Card sponsorship via PERM, DOL processing adds one to two years before an I-140 is filed.