Pay
In line with similar jobs
$203K–$274K 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 Machine Learning Engineer
Mountain View, California, United States
Actively hiring, first seen by us 1 day ago- Pay
$202,500–274,000/year · BaseAnnual period assumed — pay source
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 (see more about our compensation and benefits at Intuit®: Careers | Benefits). 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
Read the full posting- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingLead building, coding, and deploying data science models at scale
Develop, maintain, and scale web services that orchestrate ML functions for the AI team
Partner with data scientists to build pipelines that train and deploy models
Clean and prepare complex data for large-scale machine learning analysis
Run A/B tests and communicate the impact of models to leaders
From the employer’s posting
Lead the conception, coding, and deployment of data science models at scale using the latest industry tools.
Help develop, maintain, and scale web services for the AI team which orchestrate various ML functions.
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.
What you’ll bring
All qualificationsCore experience
- 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).
- 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).
Qualification wording
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).
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).
Education & alternatives
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.
Posting record
Report an errorActively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 2, 20261 day ago
- Recorded sightings
- 3
- 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 1
Early. Similar jobs usually come down between day 6 and day 69.
From 4,284 similar postings that came down. Coming down is not always a hire.
Intuit is hiring
62 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- ML Engineer hiring is picking up
- Takes jobs down quickly
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.
- Java
- Python
- Scala
- AWS
- Spark
- Keras
- pandas
- scikit-learn
- TensorFlow
Where the posting names them
- 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 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).
Your next step
Complete your application on jobs.intuit.com. The employer’s form will show what is required.
Applying through Radancy (TalentBrew)
- Radancy (TalentBrew) runs the employer’s careers site, but the application itself usually runs on another system, often Workday or Taleo. The advice for that system applies once you click Apply.
Already applied? Track this application
Has Intuit posted this job before?
Yes. We’ve followed 4 other Staff Machine Learning Engineer jobs there since April 2026. 2 came down, usually after about 88 days. 2 are still up.
Large employers often post one title for several teams, so these can be separate openings.
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
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 (see more about our compensation and benefits at Intuit®: Careers | Benefits). 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
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
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 (see more about our compensation and benefits at Intuit®: Careers | Benefits). 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
- Location & working pattern
Mountain View, California, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.