Senior Software Engineer

Adobe

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: San Jose, CA
Employment: Full-time
Posted: 40 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $164k

$109k $224k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $149,500–$177,781.

Based on 240 similar postings.

Employer

About Adobe

Adobe Inc. is a global software company known for creative and multimedia software products including Photoshop, Illustrator, Acrobat, and its cloud-based Creative Cloud and Document Cloud suites. Industry: Creative & Digital Experience Software

Adobe currently has 282 open roles on FindRole.

Listed pay typically runs $148,100–$282,100 across 76 roles with salary data.

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At a glance

TL;DR · Senior Software Engineer

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JOB TITLE: Senior Software Engineer The Senior Software Engineer joins the Adobe Risk Platform team to build fraud prevention and risk-decisioning systems for surfaces like Commerce, Stock, and Firefly. You will own the end-to-end machine learning lifecycle, including data engineering, offline model development, and real-time inference to detect and mitigate abuse. Daily responsibilities involve turning behavioral, device, and transaction signals into features, managing production APIs, SDKs, and feature stores, and monitoring model performance. You will utilize Python, SQL, PyTorch, TensorFlow, and scikit-learn, alongside production languages like Java or Go. The role requires expertise in big data tools such as Spark or Databricks to build low-latency, scalable backend services. You will solve complex business problems by transforming new fraud patterns into automated defenses using supervised/unsupervised learning and agentic AI.

What does a Software Engineer earn in California?

Median $214500 from 1193 postings across 76 companies.

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Skills

Python SQL PyTorch TensorFlow scikit-learn Spark Databricks Java Go LLMs Agentic AI APIs Distributed Services Data Pipelines Feature Stores Anomaly Detection Supervised Learning Unsupervised Learning

What you'll do

Own the end-to-end ML lifecycle including data engineering, offline model development, and real-time inference.
Build machine learning models to detect and mitigate fraud, risk, and abuse across high-volume surfaces.
Convert behavioral, device, and transaction signals into actionable features for sharper detection.
Develop and maintain a low-latency platform featuring APIs, SDKs, and feature stores.
Monitor and tune production models to maintain precision, recall, and business impact.
Experiment with new technologies including LLMs and agentic AI to improve fraud detection.
Translate new fraud patterns into technical defenses in partnership with Trust & Safety teams.

What we're looking for

Bachelor's or Master's in Computer Science, Statistics, ML, or related field, or equivalent experience.
Deep experience with ML techniques like supervised/unsupervised learning and anomaly detection applied to fraud or risk detection.
5+ years of experience building production ML systems and scalable backend services.
Fluency in Python and SQL, with proficiency in ML frameworks like PyTorch, TensorFlow, or scikit-learn.
Proficiency in a production language such as Java or Go.
Experience with big data tools like Spark or Databricks for training and serving at scale.
Strong platform engineering skills including APIs, distributed services, and low-latency data pipelines.
Experience with real-time scoring, device fingerprinting, or using LLMs/agentic AI for fraud detection (preferred).

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