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 will 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 postingBuild pipelines to train and deploy models, and create machine learning ready features
Partner with AI scientists to implement, refine and design machine learning algorithms
Run regular A/B tests and draw conclusions on the impact of your models
Monitor and maintain production models
Explore new technology shifts and how they connect to customer benefits
From the employer’s posting
build pipelines to train and deploy models
Partner with AI scientists to understand, implement, refine and design machine learning and other algorithms.
Run regular A/B tests, gather data, and draw conclusions on the impact of your models.
Monitor and maintain production models.
Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.
What you’ll bring
All qualificationsCore experience
- 7+ years of experience
- BS, MS, or PhD in Computer Science or related field, or equivalent work experience
- Experience deploying highly scalable software supporting millions or more users
- Knowledge of data science tools such as Python, TensorFlow, Spark and Pandas
- Experience integrating applications and platforms with cloud technologies such as AWS and GCP
Qualification wording
7+ years of experience
BS, MS, or PhD degree in Computer Science or related field, or equivalent work experience.
Experience deploying highly scalable software supporting millions or more users
Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark).
Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP)
Education & alternatives
Qualifications - BS, MS, or PhD degree in Computer Science or related field, or equivalent work experience. - 7+ years of 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 4,296 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.
- Python
- R
- SQL
- AWS
- GCP
- Spark
- Keras
- NumPy
- pandas
- scikit-learn
- TensorFlow
Where the posting names them
- 7+ years of experience - Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark). - Knowledge of machine learning techniques (i.e. classification, regression, and clustering).
- Understand machine learning principles (training, validation, etc.) - Knowledge of data query and data processing tools (i.e. SQL) - Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).
- Experience deploying highly scalable software supporting millions or more users - Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP) - Strong oral and written communication skills. Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users
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 Intuit as a Staff Machine Learning Engineer!
In this role, you’ll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You’ll be expected to help conceive, code, and deploy models at scale using the latest industry tools. Important skills include creating data pipelines, developing and deploying models, and machine learning operations.
Responsibilities
- Work with AI scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
- Build 'machine learning ready' feature pipelines.
- Partner with AI scientists to understand, implement, refine and design machine learning and other algorithms.
- Run regular A/B tests, gather data, and draw conclusions on the impact of your models.
- Monitor and maintain production models.
- Work cross functionally with product managers, AI scientists and product engineers, and communicate results to peers and leaders.
- Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.
Qualifications
- BS, MS, or PhD degree in Computer Science or related field, or equivalent work experience.
- 7+ years of experience
- Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark).
- Knowledge of machine learning techniques (i.e. classification, regression, and clustering).
- Understand machine learning principles (training, validation, etc.)
- Knowledge of data query and data processing tools (i.e. SQL)
- Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).
- Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
- Experience deploying highly scalable software supporting millions or more users
- Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP)
- Strong oral and written communication skills. Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users
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 (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 will 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.