Principal Engineer - Machine Learning & Inference Engineering

Wells Fargo

Quick summary

Work type
On-site
Location
Concord, CASan Francisco, CACharlotte, NC
Salary
$159,000–$305,000 / yr
Posted
3 days ago
Closes
Jul 3, 2026
Nearby
99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $217k
This role $232k
$141k most similar roles pay here $323k

This role pays more than 62% of similar roles. Most pay $183,733–$249,750 — the shaded band above. At the midpoint, this role pays about $232k versus about $217k for comparable roles.

Based on 240 similar postings.

Employer

About Wells Fargo

Wells Fargo & Company is one of the largest banks in the United States, providing banking, investment, mortgage, and consumer and commercial finance products and services nationwide. Industry: Banking & Financial Services

Wells Fargo currently has 75 open roles on FindRole.

Listed pay typically runs $152,009–$239,000 across 46 roles with salary data.

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View all roles at Wells Fargo

At a glance

TL;DR · Principal Engineer - Machine Learning & Inference Engineering

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Wells Fargo is hiring a Principal Engineer for its Digital Technology and Innovation group to lead the design, development, and operationalization of enterprise-scale AI/ML solutions across hybrid environments. This role involves driving the evolution of the Tachyon Predictive AI Platform on GCP Vertex AI, Azure ML, and On-Prem AIML Platform, overseeing end-to-end ML lifecycle management, leading model migration initiatives from legacy systems to cloud-native platforms, and integrating generative and agentic AI into workflows. The Principal Engineer will work with data scientists, MLOps engineers, and application teams to deliver innovative solutions while providing technical guidance and mentorship. Required skills include deep expertise in Python, Java, Shell scripting, Terraform, OpenShift Container Platform, Ansible, and cloud AI platforms like GCP Vertex AI and Azure ML, along with experience in Generative AI, RAG pipelines, and agentic AI systems.

Skills

Python Terraform Google Cloud Platform Azure ML Ansible GitHub Actions Generative AI RAG pipelines Agentic AI Vertex AI TensorFlow PyTorch MLOps LangGraph Crew AI Microsoft AutoGen LangChain Chainlit OpenShift Container Platform Prometheus Grafana

What you'll do

  • Lead the design, development, and operationalization of enterprise-scale AI/ML solutions on hybrid environments.
  • Oversee end-to-end ML lifecycle including feature engineering, model validation, deployment, and monitoring.
  • Drive model migration from legacy systems to cloud-native platforms like GCP Vertex AI and Azure ML.
  • Implement proactive event-driven model monitoring and drift detection for continuous improvement.
  • Automate governance processes and optimize operational SLAs in AI/ML projects.

What we're looking for

  • 5+ years of hands-on experience with cloud AI platforms (GCP Vertex AI, Azure ML)
  • Deep expertise in enterprise-grade automation solutions using tools like Ansible, Harness CD, GitHub Actions
  • Proven track record in designing and implementing full-stack agentic AI automations
  • Experience leading model migration from on-prem to cloud-native environments
  • Strong programming skills in Python, SQL/NoSQL, and proficiency with ML frameworks (TensorFlow, PyTorch)
  • Demonstrated ability to drive innovation and automation initiatives for Generative AI and agentic systems
  • Expertise in managing the end-to-end ML lifecycle including deployment and monitoring

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