Principal ML Engineer
Wells Fargo & CompanyTurn Enterprise Process Data into Intelligence at Scale
COO Technology operates at the center of the enterprise, enabling the Chief Operating Office to execute with precision, resilience, and confidence. Supporting everything from operational execution and regulatory assurance to customer experience, shared services, and supply chain, this organization is redefining how complex operations are understood, optimized, and continuously improved through data and technology.
We are seeking a Senior Lead AI Engineer to help unlock the intelligence hidden within enterprise process data. In this role, you will sit at the intersection of Analysis & Evaluation and Process Improvement, applying advanced ML techniques to transform raw, extracted operational data into clear insights about how work actually gets done—and how it can be done better. Your work will power pattern discovery, process similarity analysis, and execution conformity at enterprise scale, directly influencing AI‑driven transformation initiatives across the firm.
You will design scalable agentic solutions, ML systems that reconcile fragmented entities, surface meaningful clusters of behavior, and extract canonical execution patterns from clickstream data, documents, and knowledge graphs. By enriching enterprise knowledge graphs with continuously learned insights and measuring real‑world execution against documented procedures, you will enable a new level of process transparency, accountability, and automation.
This is a high‑impact opportunity for someone who wants to shape how machine learning drives measurable operational improvement across a complex, regulated environment.
In this role, you will:
Entity Deduplication & Resolution: Design and implement scalable ML pipelines for entity deduplication across knowledge graphs, handling entities extracted from diverse sources (transcripts, documents, structured data).
Intelligent Clustering: Build clustering algorithms to identify similar patterns across processes, participants, and execution paths.
Pattern Extraction: Develop ML models to extract canonical patterns of process execution from clickstream data and. documentation.
Knowledge Graph Enrichment: Create ML-powered pipelines that continuously enrich knowledge graphs with discovered patterns, relationships, and insights.
Conformity Analysis: Build models to calculate and analyze conformity scores comparing actual process execution against documented procedures.
Scalable Architecture: Design ML solutions that operate at enterprise scale, handling large volumes of process data and documentation.
Cross-Workstream Collaboration: Work with Analysis & Evaluation team on pattern discovery from clickstream data and with Process Improvement team on process similarity analysis.
Required Qualifications:
7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education.
3+ years of experience with clustering algorithms and unsupervised learning techniques for pattern discovery.
2+ years of experience working with knowledge graphs or graph-based ML techniques.
5+ years of experience with Python with experience in ML frameworks.
Desired Qualifications:
Experience with agentic data retrieval and analysis at the Enterprise Level.
3+ years of experience building entity resolution, deduplication, or record linkage systems at scale.
Expertise in NLP techniques for semantic similarity, text clustering, and information extraction.
Experience with graph databases.
Background in process mining, conformance checking, or business process analysis.
Experience with LLMs and embedding models for semantic similarity.
Experience building ML pipelines using MLOps best practices.
Experience with cloud computing platforms.
Experience with distributed computing frameworks.
Knowledge of containerization and orchestration technologies.
Experience in financial services or operations domains.
Excellent communication skills across technical and non-technical audiences.
Advanced degree (M.S. or Ph.D.) in Computer Science, Machine Learning, or related field.
Job Expectations and Core Values:
Be Humble: You're smart yet always interested in learning from others.
Work Transparently: You always deal in an honest, direct, and transparent way.
Take Ownership: You embrace responsibility and find joy in having the answers.
Learn More: You regularly self-educate and improve your skill set.
Show Gratitude: You show appreciation and respect to those you work with.
Pay Range
Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to demonstrated examples of prior performance, skills, experience, or work location. Employees may also be eligible for incentive opportunities.
$159,000.00 - $305,000.00Benefits
Wells Fargo provides eligible employees with a comprehensive set of benefits, many of which are listed below. Visit Benefits - Wells Fargo Jobs for an overview of the following benefit plans and programs offered to employees.
- Health benefits
- 401(k) Plan
- Paid time off
- Disability benefits
- Life insurance, critical illness insurance, and accident insurance
- Parental leave
- Critical caregiving leave
- Discounts and savings
- Commuter benefits
- Tuition reimbursement
- Scholarships for dependent children
- Adoption reimbursement
Posting End Date:
1 May 2026*Job posting may come down early due to volume of applicants.
We Value Equal Opportunity
Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.
Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit’s risk appetite and all risk and compliance program requirements.
Applicants with Disabilities
To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.
Drug and Alcohol Policy
Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.
Wells Fargo Recruitment and Hiring Requirements:
a. Third-Party recordings are prohibited unless authorized by Wells Fargo.
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.