Staff Machine Learning Engineer

Intuit

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Mountain View, CA
Salary
$202,500–$274,000 / yr
Posted
5 days ago
Freshness
Confirmed live today

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $230k
This role $238k
$173k $294k
below market most similar roles pay here above market

This role pays less than 53% of similar roles. Most pay $206,175–$254,750 — the blue band above. At the midpoint, this role pays about $238k versus about $230k for comparable roles.

Based on 240 similar postings.

Employer

About Intuit

Intuit is a financial software company known for products like TurboTax, QuickBooks, Mint, and Credit Karma, helping consumers and small businesses manage their finances and taxes. Industry: Financial Software & Technology

Intuit currently has 255 open roles on FindRole.

Listed pay typically runs $202,500–$274,000 across 236 roles with salary data.

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At a glance

TL;DR · Staff Machine Learning Engineer

The Staff Machine Learning Engineer joins the Fintech Risk AI/ML Smart Money Services team to detect and prevent fraud and financial risk for all Money Movement events. In this role, you will lead the conception, coding, and deployment of data science models at scale while developing and maintaining web services that orchestrate various machine learning functions. You will partner with data scientists to build robust pipelines, extract data from complex sources, and run regular A/B tests. Key technical requirements include proficiency in Python, Scala, or Java, along with experience using Scikit, Pandas, TensorFlow, Keras, and Spark. You must demonstrate expertise in supervised and unsupervised learning, Generative AI, and GPU acceleration using CUDA and cuDNN within AWS cloud environments.

What does a Machine Learning Engineer earn in California?

Median $235750 from 200 postings across 34 companies.

See salary data

What you'll do

  • Lead the conception, coding, and deployment of data science models at scale.
  • Develop, maintain, and scale web services that orchestrate various ML functions.
  • Process and clean data from complex sources to make it machine learning-ready.
  • Build robust pipelines to train and deploy models in partnership with data scientists.
  • Run regular A/B tests and communicate the impact of models to stakeholders.
  • Work with divergent data types and big data scales reaching petabytes.
  • Explore new technology shifts to identify potential customer benefits.

What we're looking for

  • 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 in Object-Oriented Languages such as Python, Scala, or Java.
  • Deep knowledge of Data Science tools and frameworks including Scikit, Pandas, TensorFlow, Keras, and Spark.
  • Strong software engineering fundamentals including data structures, algorithms, performance complexity, and version control systems like Git.
  • Demonstrated experience with web services (e.g., REST) and API design.
  • Experience integrating applications with cloud technologies (e.g., AWS) and deploying scalable software for millions of users.
  • Practical experience with Supervised/Unsupervised ML, Generative AI (autoencoders, GANs, VAEs), and GPU acceleration (CUDA and cuDNN).

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