Sr Machine Learning Engineer

PayPal

Hybrid

Quick summary

Work type: Hybrid
Location: Austin, TX
Salary: $117,500–$199,500 / yr
Posted: 3 days ago
Closes: Jun 30, 2026
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $217k

This role $158k

$100k most similar roles pay here $280k

This role pays less than 90% of similar roles. Most pay $184,412–$249,750 — the shaded band above. At the midpoint, this role pays about $158k versus about $217k for comparable roles.

Based on 240 similar postings.

Employer

About PayPal

PayPal is a leading global digital wallet and online payment system, founded in 1998, that allows individuals and businesses to send, receive, and manage funds securely in over 200 markets.

PayPal currently has 47 open roles on FindRole.

Listed pay typically runs $160,500–$236,500 across 47 roles with salary data.

Most-posted roles

View all roles at PayPal

At a glance

TL;DR · Sr Machine Learning Engineer

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Senior Machine Learning Engineers at PayPal in Austin, TX are integral to evaluating and validating high-impact statistical and AI/ML models across critical business areas. They perform comprehensive model validation aligned with internal Model Risk Management policies and industry standards, ensuring data integrity, design soundness, and performance robustness. Day-to-day responsibilities include building scalable systems using Python and cloud platforms, architecting end-to-end pipelines for real-time data ingestion and monitoring, and mentoring junior engineers while integrating cutting-edge deep learning techniques. Candidates must have experience with algorithms like logistic regression and random forests, deep learning architectures such as CNNs and RNNs, and proficiency in Python libraries including pandas, scikit-learn, TensorFlow, and PyTorch, along with SQL for large-scale data analytics.

Skills

Python TensorFlow PyTorch pandas scikit-learn SQL CNNs RNNs LLMs Model Risk Management (MRM) AWS Kubernetes CI/CD Prometheus Grafana

What you'll do

Evaluate and validate high-impact statistical and AI/ML models across business areas.
Design sound machine learning systems using Python and cloud platforms for real-time data ingestion.
Conduct comprehensive model validation to ensure regulatory compliance and risk management.
Mentor junior engineers and integrate cutting-edge deep learning methods in projects.
Build scalable end-to-end pipelines for model serving, monitoring, and continuous improvement.

What we're looking for

Master’s degree in Data Science, Computer Science, or related field plus 2 years of experience.
Design and implement scalable machine learning models using logistic regression, random forests, gradient boosting, and time series models.
Utilize deep learning architectures like CNNs, RNNs, and large language models for automation and decision-making.
Conduct exploratory data analysis, statistical modeling, and visualization to inform model improvements.
Program in Python with libraries such as pandas, scikit-learn, TensorFlow, and PyTorch for model development and validation.
Develop and validate AI/ML models for risk management, fraud detection, AML, and compliance standards.

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Go Python PyTorch TensorFlow JAX Kubernetes Jenkins CI/CD

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