Senior Machine Learning Engineer, Credit Risk

Intuit

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Quick summary

Work type: On-site
Location: Mountain View, CA
Salary: $171,000–$231,500 / yr
Posted: 1 day ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $226k

This role $201k

$158k most similar roles pay here $290k

This role pays less than 73% of similar roles. Most pay $197,687–$254,750 — the shaded band above. At the midpoint, this role pays about $201k versus about $226k 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 210 open roles on FindRole.

Listed pay typically runs $202,500–$274,000 across 187 roles with salary data.

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At a glance

TL;DR · Senior Machine Learning Engineer, Credit Risk

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As a Senior Machine Learning Engineer, you will join Team Apollo within the Fintech Risk AI/ML credit risk team to detect and prevent credit risk for lending money movement services products. You will work alongside data scientists to conceive, code, and deploy data science models at scale while developing and maintaining web services that orchestrate various machine learning functions. Your daily responsibilities include data wrangling, feature engineering, and building pipelines to train and deploy models. You will perform statistical analysis, run A/B tests, and manage data sources. Required technical skills include Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark, and SQL. You must also possess experience with REST APIs, Scala, Java, Git, AWS, and GPU acceleration using CUDA and cuDNN to ensure production-ready software performance.

What does a Machine Learning Engineer earn in California?

Median $231150 from 183 postings across 28 companies.

See salary data

Skills

Python SQL AWS TensorFlow Keras Spark Pandas Numpy NLTK Java Scala REST API Design Git CUDA cuDNN R

What you'll do

Conceive, code, and deploy data science models at scale using industry-standard tools.
Develop and maintain web services to orchestrate various machine learning functions.
Perform data wrangling, feature engineering, and model testing to prepare data for machine learning.
Build automated pipelines to train and deploy machine learning models.
Run regular A/B tests and perform statistical analysis to evaluate model impact.
Discover, import, and clean data sources to make them machine learning ready.
Design and implement machine learning algorithms in partnership with data scientists.

What we're looking for

BS, MS, or PhD degree in Computer Science or related field, or equivalent work experience.
6+ years of experience.
Knowledge of Data Science tools and frameworks including Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, and Spark.
Understanding of machine learning principles such as training and validation.
Demonstrated experience with web services (e.g. REST) and API design.
Experience with Object Oriented Languages (OOD) such as Scala, Python, or Java (preferred).
Knowledge of data query and data processing tools like SQL.
Experience deploying highly scalable software supporting millions or more users.

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