APPLICANTS WITH DISABILITIES

To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo .

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

Required Qualifications:

• 5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• 5+ years of hands-on programming experience with either Java, C#, and/or python
• 3+ Experience with data pre-processing, feature engineering, and model evaluation
• 2+ years experience designing, developing, and deploying Machine Learning technolog

Desired Qualifications:

• Experience with NLP techniques such as tokenization, embeddings, transformers, and attention mechanisms
• Strong understanding of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Hugging Face Transformers)
• Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes)
• Experience with data preprocessing, feature engineering, and model evaluation
• Experience with deploying machine learning models in production environments and integrating ML into applications
• Knowledge of MLOps practices and tools
• Knowledge of Rule Engine Technolog

Wells Fargo is seeking a Lead Software Engineer in our Architecture and Engineering Group as part of Consumer Technology. Learn more about the career areas and business divisions at wellsfargojobs.com.

• AI Development: Design, develop, and implement advanced AI algorithms and models to solve complex business problems
• Machine Learning Expertise: Apply machine learning techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning, to create innovative solutions
• Data Analysis: Perform data preprocessing, feature engineering, and exploratory data analysis to prepare datasets for AI model training
• Collaboration: Work closely with data scientists, product managers, and other engineers to integrate AI solutions into existing systems and products
• Performance Optimization: Optimize AI models for performance, scalability, and efficiency in production environments
• Project Management: Participate in project planning, estimation, and execution, ensuring timely delivery of AI features and enhancements
• Code Quality: Write clean, maintainable, and efficient code following best practices and coding standards

In this role, you will:

• Lead complex technology initiatives including those that are companywide with broad impact
• Act as a key participant in developing standards and companywide best practices for engineering complex and large scale technology solutions for technology engineering disciplines
• Design, code, test, debug, and document for projects and programs
• Review and analyze complex, large-scale technology solutions for tactical and strategic business objectives, enterprise technological environment, and technical challenges that require in-depth evaluation of multiple factors, including intangibles or unprecedented technical factors
• Make decisions in developing standard and companywide best practices for engineering and technology solutions requiring understanding of industry best practices and new technologies, influencing and leading technology team to meet deliverables and drive new initiatives
• Collaborate and consult with key technical experts, senior technology team, and external industry groups to resolve complex technical issues and achieve goals
• Lead projects, teams, or serve as a peer mentor

Required Qualifications:

• 5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• 5+ years of hands-on programming experience with either Java, C#, and/or python
• 3+ Experience with data pre-processing, feature engineering, and model evaluation
• 2+ years experience designing, developing, and deploying Machine Learning technology

Desired Qualifications:

• Experience with NLP techniques such as tokenization, embeddings, transformers, and attention mechanisms
• Strong understanding of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Hugging Face Transformers)
• Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes)
• Experience with data preprocessing, feature engineering, and model evaluation
• Experience with deploying machine learning models in production environments and integrating ML into applications
• Knowledge of MLOps practices and tools
• Knowledge of Rule Engine Technology