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Understanding the role of a senior software AI/ML quality engineer
The position of a Senior Software AI/ML Quality Engineer at Wells Fargo is pivotal in ensuring the quality and performance of digital platforms and financial products. This role requires a blend of technical expertise and collaborative spirit. As a senior engineer, you will work alongside a talented engineering team, aiming to deliver products that not only meet but exceed customer expectations. This is essential for speeding up development cycles while maintaining high-quality standards.
Key responsibilities of a senior software AI/ML quality engineer
In this role, you will:
- Lead complex initiatives within technical environments, ensuring all deliverables meet quality benchmarks.
- Contribute to strategic planning for large-scale projects, which helps in effective resource allocation and project execution.
- Engage in the design, coding, testing, and documentation processes associated with technology domains.
- Address technical challenges, requiring a thorough evaluation of technologies and procedures.
- Resolve issues while leading a team to fulfill existing and prospective client needs, leveraging a solid understanding of compliance requirements.
- Collaborate effectively with peers and colleagues to overcome technical obstacles and achieve project goals.
- Guide less experienced staff while acting as a pivotal point of escalation during project execution.
Required qualifications for the position
To excel in this role, certain qualifications are essential:
- A minimum of 4 years of experience in Software Engineering or an equivalent combination of experience, training, and education.
- At least 3 years of experience with programming languages like Java and C#, as well as APIs.
- Experience in designing, developing, and deploying applications powered by large language models (LLMs) for at least 2 years.
- Familiarity with natural language processing (NLP) techniques such as tokenization, embeddings, transformers, and attention mechanisms for at least 1 year.
Desired qualifications that enhance your application
While not mandatory, having the following qualifications can set you apart:
- A strong grasp of machine learning frameworks and libraries like TensorFlow, PyTorch, and Hugging Face Transformers.
- Experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).
- A background in data preprocessing, feature engineering, and model evaluation.
- Experience deploying machine learning models in production and integrating them into applications.
- Knowledge of ML Ops practices and tools.
- Familiarity with Rule Engine Technology.
Job expectations for a senior software AI/ML quality engineer
This role encompasses various expectations that align with the company’s strategic goals:
- AI Development: Design and implement AI algorithms and models to tackle complex business challenges.
- Machine Learning Knowledge: Utilize machine learning techniques, including deep learning and reinforcement learning, to develop innovative solutions.
- Data Analysis: Conduct data preprocessing, feature engineering, and exploratory data analysis to prepare datasets for AI model training.
- Performance Optimization: Enhance AI models for performance, scalability, and efficiency in production environments.
- Project Management: Engage in project planning and execution, ensuring the timely delivery of AI features and enhancements.
- Code Quality: Write clean and maintainable code adhering to best practices and standards.
Understanding the application process
It’s important to note that this position does not offer Visa sponsorship, so applicants must have the legal right to work in the specified location. The pay range for this position is competitive and reflects the base pay offered, which may vary based on individual qualifications and experience.
Wells Fargo’s commitment to equal opportunity
Wells Fargo values diversity and is committed to providing equal employment opportunities. All qualified applicants will be considered for employment regardless of race, color, religion, gender, sexual orientation, national origin, disability, or veteran status. Employees are expected to follow comprehensive risk programs and adhere to company policies to ensure a successful and compliant workplace.