Machine Learning Engineer

About the Company

Wells Fargo is a global financial services company committed to delivering innovative technology solutions that enhance operational excellence and customer experiences. Within the Chief Operating Office (COO) Technology organization, the Cognitive AI Solutions team develops enterprise-scale AI platforms that leverage machine learning, multimodal data, and intelligent automation to transform complex business processes into actionable insights.

About the Role

The Principal Machine Learning Engineer is responsible for designing, building, and scaling enterprise AI platforms that enable process intelligence and autonomous AI solutions. This role combines expertise in machine learning, software architecture, data engineering, and AI systems to develop reusable platform capabilities that support multiple business functions across a highly regulated enterprise environment.

Location: Irving, Texas (Onsite)

Key Responsibilities

Machine Learning Platform Development

• Design and architect scalable machine learning platforms for enterprise-wide AI applications.
• Develop reusable components, APIs, and frameworks that accelerate AI solution development.
• Build production-ready ML systems capable of supporting multiple business use cases.
• Ensure platform scalability, reliability, and maintainability.

AI & Process Intelligence

• Develop machine learning solutions that analyze enterprise process data from multiple structured and unstructured sources.
• Design systems that discover, model, and optimize operational workflows.
• Apply advanced machine learning techniques to identify patterns, anomalies, and process improvements.
• Build intelligent systems that continuously learn from enterprise data.

Multimodal AI & Agent Development

• Develop AI pipelines that process documents, clickstream data, videos, transcripts, and system logs.
• Design autonomous AI agent architectures, orchestration frameworks, and intelligent tool integrations.
• Build knowledge graph and memory-based systems that enhance AI reasoning capabilities.
• Implement entity resolution, semantic analysis, and information extraction solutions.

Data Engineering & MLOps

• Design scalable ML pipelines using modern MLOps best practices.
• Develop evaluation frameworks, monitoring tools, and production observability solutions.
• Optimize model deployment, performance, and lifecycle management.
• Ensure enterprise-grade reliability, governance, and compliance for AI solutions.

Technical Leadership

• Establish engineering standards and architecture best practices across AI initiatives.
• Mentor engineers and provide technical leadership for complex machine learning projects.
• Collaborate with Product, Engineering, Data Science, and business stakeholders.
• Drive innovation while delivering high-quality production solutions.

Qualifications

Required

• Minimum of 7 years of software engineering or machine learning engineering experience.
• At least 5 years of professional Python development experience.
• Experience with machine learning frameworks and production ML systems.
• Strong knowledge of clustering algorithms and unsupervised learning techniques.
• Experience working with knowledge graphs or graph-based machine learning.
• Strong software architecture, system design, and problem-solving skills.
• Excellent communication and stakeholder collaboration abilities.

Preferred

• Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• Experience building enterprise AI agents and autonomous systems.
• Expertise in natural language processing (NLP), semantic similarity, and information extraction.
• Experience with large language models (LLMs) and embedding models.
• Knowledge of graph databases and graph-based analytics.
• Experience with entity resolution, record linkage, or deduplication systems.
• Familiarity with process mining and business process analysis.
• Experience implementing MLOps best practices.
• Experience with cloud platforms, distributed computing, containerization, and orchestration technologies.
• Background in financial services or regulated enterprise environments.

Benefits

• Comprehensive medical, dental, and vision insurance.
• 401(k) retirement plan.
• Paid time off and parental leave.
• Disability, life, and critical illness insurance.
• Critical caregiving leave.
• Tuition reimbursement.
• Scholarships for dependent children.
• Adoption reimbursement.
• Employee discounts and commuter benefits.
• Performance-based incentive opportunities.
• Career development within a global financial institution.

Ideal Candidate

This opportunity is ideal for professionals who:

• Have extensive experience designing enterprise-scale machine learning platforms.
• Enjoy solving complex AI, data engineering, and system architecture challenges.
• Thrive in collaborative, fast-paced environments.
• Are passionate about building production-ready AI systems that deliver measurable business impact.
• Demonstrate strong technical leadership, innovation, and continuous learning.

Equal Opportunity Employer

Wells Fargo is committed to fostering an inclusive workplace and providing equal employment opportunities to all qualified applicants regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by applicable law.