Staff Machine Learning Engineer
Mountain View, California
- 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 the conception, coding, and deployment of data science models at scale using the latest industry tools.
Partner closely with data scientists to understand, implement, and refine algorithms, building robust pipelines to train and deploy models.
From the employer’s posting
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.
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.
Tools in this posting
- Java
- Python
- Scala
- AWS
- Spark
- Keras
- pandas
- scikit-learn
- TensorFlow
Source — Tool mentions in context
- 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).
Posting record
Report an errorActively hiringFirst seen by us 7 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 22, 2026 · 7 days ago
- Recorded sightings
- 50
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
Complete your application on jobs.intuit.com. The employer’s form will show what is required.
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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
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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