Pay
Higher than most similar jobs
$246K–$340K against $166K–$240K, the middle half of what similar US postings state.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Staff AI/ML Engineer
San Francisco, CA, USA
Live, first seen by us 19 days ago- Pay
USD 246,000–340,000/yearAnnual period assumed — pay source
Wage Notice $246,000—$340,000 USD A little about us
Read the full posting- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingChime's Data Science & Machine Learning team builds the models, services, and platforms behind how millions of members manage and grow their financial lives.
In this role, you'll build and deploy machine learning systems on some of the richest transactional and behavioral data in fintech, turning it into the credit decisions behind products like MyPay, Instant Loans, and SpotMe.
Lead design, training, and deployment of underwriting models using transaction and cash flow data
Take models from problem framing through production, monitoring, and iteration
Design feature pipelines, batch and real-time inference, monitoring, and retraining
Partner with Product, Engineering, Analytics, and Risk on ML solutions
Set the Lending ML technical roadmap and raise team standards through reviews and mentorship
From the employer’s posting
Chime's Data Science & Machine Learning team builds the models, services, and platforms behind how millions of members manage and grow their financial lives. We're hiring a Staff AI/ML Engineer on our Lending and Cashflow team to lead the modeling behind cash flow underwriting and surface member insight: using members' transaction and deposit data to make fair, accurate credit decisions for people that traditional credit scores often miss.
In this role, you'll build and deploy machine learning systems on some of the richest transactional and behavioral data in fintech, turning it into the credit decisions behind products like MyPay, Instant Loans, and SpotMe. This is a highly applied role: you'll own problems end to end, from framing the question through to a model running in production and moving a metric that matters, and you'll set the technical direction for how Chime underwrites with cash flow data.
Lead the design, training, and deployment of deep learning and classical ML underwriting models that turn members' transaction and cash flow data into credit decisions
Take models from problem framing through to production — training, evaluation, deployment, monitoring, and iteration
Design and improve the systems around the model: feature pipelines, batch and real-time inference, monitoring, and retraining
Partner with Product, Engineering, Analytics, and Risk to turn ambiguous business problems into ML solutions
Set the technical roadmap for Lending ML and raise the bar across the team through design reviews, mentorship, and shared standards
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 16, 202619 days ago
- Recorded sightings
- 25
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 19
Similar jobs usually come down between day 6 and day 69.
From 4,362 similar postings that came down. Coming down is not always a hire.
Chime Financial is hiring
9 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- AWS
- Kafka
- Redis
- SageMaker
- Snowflake
- Spark
- Airflow
- PySpark
- PyTorch
Where the posting names them
- Comfort with messy real-world data, including label definition, leakage, class imbalance, and train/serve skew - Strong proficiency in Python and SQL, with deep learning frameworks such as PyTorch and distributed compute such as Spark or PySpark - Working knowledge of modern ML infrastructure — AWS and tools such as SageMaker, Airflow, Kafka, Redis, and Snowflake — and an MLOps mindset for keeping production systems healthy
- Strong proficiency in Python and SQL, with deep learning frameworks such as PyTorch and distributed compute such as Spark or PySpark - Working knowledge of modern ML infrastructure — AWS and tools such as SageMaker, Airflow, Kafka, Redis, and Snowflake — and an MLOps mindset for keeping production systems healthy - The ability to operate independently in ambiguous environments, influence technical direction beyond your own team, and explain model decisions clearly to engineers, risk partners, and senior leaders
Your next step
Complete your application on boards.greenhouse.io. The employer’s form will show what is required.
Applying through Greenhouse
- No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
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Already applied? Track this application
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
About the role
Chime's Data Science & Machine Learning team builds the models, services, and platforms behind how millions of members manage and grow their financial lives. We're hiring a Staff AI/ML Engineer on our Lending and Cashflow team to lead the modeling behind cash flow underwriting and surface member insight: using members' transaction and deposit data to make fair, accurate credit decisions for people that traditional credit scores often miss.
In this role, you'll build and deploy machine learning systems on some of the richest transactional and behavioral data in fintech, turning it into the credit decisions behind products like MyPay, Instant Loans, and SpotMe. This is a highly applied role: you'll own problems end to end, from framing the question through to a model running in production and moving a metric that matters, and you'll set the technical direction for how Chime underwrites with cash flow data.
In this role, you can expect to
- Lead the design, training, and deployment of deep learning and classical ML underwriting models that turn members' transaction and cash flow data into credit decisions, from approval and line assignment to loss forecasting
- Take models from problem framing through to production — training, evaluation, deployment, monitoring, and iteration — and stay accountable for how they behave once they're live
- Design and improve the systems around the model: feature pipelines, batch and real-time inference, monitoring, and retraining
- Partner with Product, Engineering, Analytics, and Risk to turn ambiguous business problems into ML solutions, and to make sure the solution is the right one
- Connect model performance to member outcomes and business metrics, and use experimentation to prove impact
- Set the technical roadmap for Lending ML and raise the bar across the team through design reviews, mentorship, and shared standards for model development, validation, and governance
- Help identify where AI/ML creates measurable impact for members — and where a simpler answer is the better one
To thrive in this role, you have
- A track record of leading the design and deployment of deep learning models in production, including multi-quarter initiatives that span teams, with a solid grasp of architecture choice, training dynamics, and evaluation, and the judgment to make model design choices
- Solid machine learning fundamentals: classical modeling, evaluation design, and knowing which metric actually answers the question in front of you
- Hands-on experience across the end-to-end ML lifecycle — training, experimentation, optimization, deployment, and monitoring
- Comfort with messy real-world data, including label definition, leakage, class imbalance, and train/serve skew
- Strong proficiency in Python and SQL, with deep learning frameworks such as PyTorch and distributed compute such as Spark or PySpark
- Working knowledge of modern ML infrastructure — AWS and tools such as SageMaker, Airflow, Kafka, Redis, and Snowflake — and an MLOps mindset for keeping production systems healthy
- The ability to operate independently in ambiguous environments, influence technical direction beyond your own team, and explain model decisions clearly to engineers, risk partners, and senior leaders
Nice-to-have
Experience in either of these is a plus:
- Credit or underwriting models, and familiarity with model governance, explainability, and fairness requirements, such as adverse action reason codes and fair lending testing
- Cash flow or alternative-data underwriting: building credit features from bank transaction data, such as income and expense detection, balance trends, and transaction categorization
- Deployed transformer models in production
#LI-Onsite #LI-DA1
Below is the base salary offered for this role and level of experience. Full-time employees may also be eligible for bonus(es), competitive equity, and benefits. For commissioned roles, the base salary listed in this job description does not include incentive/variable pay. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.
Wage Notice
$246,000—$340,000 USD
A little about us
At Chime, we believe that everyone can achieve financial progress. We created Chime—a financial technology company, not a bank*—on the premise that core banking services should be helpful, easy, and free. Through our user-friendly tools and intuitive platforms, we empower our members to take control of their finances and work towards their goals. Whether it's starting a savings account, purchasing a first car or home, launching a business, or pursuing higher education, we're proud to have helped millions unlock their financial potential.
We're a team of problem solvers, dreamers, and builders with one shared obsession: our members. From day one, Chimers have worked tirelessly to out-hustle and out-execute competitors to bring our mission to life. Their grit and determination inspire us to work harder every day to deliver the very best experience possible. We each bring an owner's mindset to our work, refusing to be outdone and holding ourselves accountable to meet and exceed the highest bars for our teams, our company, and our members.
We believe in being bold, dreaming big, and taking risks, while also working together, embracing our diverse perspectives, and giving each other honest feedback. Our culture remains deeply entrepreneurial, encouraging every Chimer to see themselves as stewards of our mission to help everyday Americans unlock their financial progress.
We know that to achieve our mission, we must earn and keep people's trust—so we hold ourselves to the highest standards of integrity in everything we do. These aren't just words on a wall—our values are embedded in every aspect of our business, serving as a north star that guides us as we work to help millions achieve their financial potential.
Because if we don't—who will?
*Chime is a financial technology company, not a bank. Banking services provided by The Bancorp Bank, N.A. or Stride Bank, N.A., Members FDIC.
What we offer for our full-time, regular employees
- 🏢 Our in-office work policy is designed to keep you connected - with four days a week in the office and Fridays from home for those near one of our offices, plus team and company-wide events depending on location. Whether you’re coming in regularly or are part of our fully remote program, you’ll stay engaged with your work and teammates.
- 💻 Benefits that support your work and life, including backup child, elder, and pet care and subsidized commuter benefits for eligible employees.
- ✨ Comprehensive health, financial, and wellbeing benefits designed to support you at every stage of life.
- 🏝 Generous vacation policy and company-wide paid days off
- 🫂 1% of your time off to support local community organizations of your choice
- 👟 Annual wellness stipend to use towards eligible wellness related expenses
- 👶 Up to 22 weeks of paid parental leave for birthing parents and 12 weeks of paid parental leave for non-birthing parents
- 👪 Access to family planning reimbursement
- 💚 A challenging and fulfilling opportunity to join one of the most experienced teams in FinTech and help millions unlock financial progress
We know that great work can’t be done without a diverse team and inclusive environment. That’s why we specifically look for individuals of varying strengths, skills, backgrounds, and ideas to join our team. We believe this gives us a competitive advantage to better serve our members and helps us all grow as Chimers and individuals.
Chime is proud to be an Equal Opportunity Employer. We consider qualified applicants without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, genetic information, veteran status, or any other legally protected basis under provincial, federal, state, and local laws, regulations, or ordinances. We will also consider qualified applicants with criminal histories in a manner consistent with the requirements of state and local laws, including the San Francisco Fair Chance Ordinance, Cook County Ordinance, NYC Fair Chance Act, and the LA City Fair Chance Ordinance, and consistent with Canadian provincial and federal laws. If you have a disability or special need that requires accommodation during any stage of the application process, please contact: accommodations@chime.com.
To learn more about how Chime collects and uses your personal information during the application process, please see the Chime Applicant Privacy Notice.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Wage Notice $246,000—$340,000 USD A little about us
- Location & working pattern
San Francisco, CA, USA
What we offer for our full-time, regular employees - 🏢 Our in-office work policy is designed to keep you connected - with four days a week in the office and Fridays from home for those near one of our offices, plus team and company-wide events depending on location. Whether you’re coming in regularly or are part of our fully remote program, you’ll stay engaged with your work and teammates. - 💻 Benefits that support your work and life, including backup child, elder, and pet care and subsidized commuter benefits for eligible employees.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.