Key skills
AWSAzureCloudAIMachine LearningGenerative AILarge Language ModelsAnalyticsGoogle CloudProblem SolvingCollaboration
About this role
Role Overview
- Apply prompt engineering techniques to enhance AI model performance for customer service automation
- Collaborate with cross-functional teams to integrate AI-driven enhancements into production systems
- Support the development and optimization of AI models to meet operational goals
- Contribute to the architecture of AI systems to improve customer interactions
- Ensure the reliability, accuracy, and efficiency of AI applications in customer service operations
- Fine-tune AI models to enhance performance and user satisfaction
- Also responsible for other duties/projects as assigned by business management as needed
Requirements
- Bachelor's Degree OR combination of education and experience deemed equivalent
- Less than 2 years Developing and optimizing AI models, particularly in customer service automation
- Less than 2 years Applying AI techniques such as prompt engineering and fine-tuning
- Less than 2 years Collaborating with cross-functional teams to integrate AI-driven solutions into production systems
- Data Analysis: Ability to analyze and interpret complex data to improve AI model performance
- Problem Solving: Strong problem-solving skills to troubleshoot and optimize AI systems
- Collaboration: Excellent collaboration skills to work effectively with cross-functional teams
- Data Management: Ability to work with structured and unstructured datasets while ensuring data accuracy, integrity, security, and compliance with organizational standards
- Data Modeling: Understanding of data modeling concepts and techniques, including relational, dimensional, and semantic data models used to support analytics, machine learning, and AI applications
- Model Tuning: Ability to analyze model performance, identify improvement opportunities, and implement adjustments to enhance accuracy, reliability, and scalability
- Prompt Engineering: Knowledge of prompt engineering best practices for generative AI and large language models (LLMs), including prompt design, testing, refinement, and optimization
- Cloud Computing: Knowledge of cloud computing platforms and services (e.g., AWS, Azure, Google Cloud) used for data processing, machine learning, and AI solution deployment.
Tech Stack
- AWS
- Azure
- Cloud
Benefits
- medical, dental and vision insurance
- flexible spending account
- 401(k)
- employee stock grants
- employee stock purchase plan
- paid time off and up to 12 paid holidays
- paid parental and family leave
- family building benefits
- back-up care
- enhanced family support
- childcare subsidy
- tuition assistance
- college coaching
- short
- and long-term disability
- voluntary AD&D coverage
- voluntary accident coverage
- voluntary life insurance
- voluntary disability insurance
- voluntary long-term care insurance
- mobile service & home internet discounts
- pet insurance
- access to commuter and transit programs