AI Quality Engineer- Sous Chef

As an AI Quality Engineer - Sous Chef at Toast, you'll be integral to refining our AI assistant's responses and ensuring quality across our product. Your responsibilities include evaluating user feedback, testing backend APIs and frontend experiences, and shaping the AI's knowledge base to enhance its performance. You'll be involved in crafting delightful user experiences while working closely with cross-functional teams, making a significant impact on how restaurants operate.

To excel as an AI Quality Engineer - Sous Chef at Toast, you should have a minimum of 3 years of experience in QA, engineering, or product operations. Strong analytical and problem-solving skills, combined with excellent communication abilities, are crucial. Additionally, familiarity with AI tools, experience in testing backend systems, and a background in the restaurant or hospitality industry are highly valued.

The AI Quality Engineer - Sous Chef position at Toast is unique because it allows you to be part of a foundational team focused on an AI-driven product in its early stages. You'll enjoy cross-functional collaboration while influencing both backend architecture and fine-tuned AI behavior, making your work critical to enhancing how restaurants thrive in a challenging environment.

In your role as an AI Quality Engineer - Sous Chef at Toast, you’ll directly influence the customer experience by ensuring that our Sous Chef assistant delivers accurate, helpful, and engaging responses. This directly supports restaurant owners in making informed decisions, streamlining their operations and improving overall guest experiences, ultimately helping them grow their businesses.

The team culture for the AI Quality Engineer - Sous Chef role at Toast is built on collaboration, flexibility, and a shared commitment to the restaurant community. We embrace diversity and inclusion, fostering a supportive environment where everyone’s contributions are valued. You'll be encouraged to innovate and thrive, all while collaborating closely with engineers, designers, and other experts in a hybrid work setting.

To ensure the quality of AI responses, I focus on understanding user feedback and continuously evaluating performance metrics. I also implement comprehensive testing procedures, including both automated and manual testing, to identify any weaknesses in the AI model and adjust the training data accordingly to improve its responses.

In AI projects, I commonly use tools like Postman for API testing, Jira for tracking issues, and various test automation platforms to streamline processes. These tools help ensure that every component of the product is functioning correctly and that we can efficiently address any issues that arise.

In a previous QA role, I encountered a significant issue where our AI model consistently misinterpreted user commands. To resolve this, I collaborated with the engineering team to analyze the algorithms, reviewed our training data for gaps, and created a series of new test cases that helped us refine the model's understanding, significantly reducing errors.

When managing multiple fast-moving workstreams, I prioritize tasks based on their impact on project goals and deadlines. I often utilize agile methodologies, breaking down tasks into smaller, manageable parts, and regularly communicate with the team to reassess priorities and ensure we are aligned on critical objectives.

Essential skills for an AI Quality Engineer - Sous Chef include strong analytical abilities, effective communication, and a solid understanding of AI technologies. It's also important to have a keen interest in the restaurant industry, as it enables a better understanding of user needs, as well as experience with QA tools and methodologies.

Metadata plays a critical role in AI training as it provides context to the data used for model development. It can include information about data quality, origin, and relevance, allowing developers to refine AI behavior based on insights derived from this additional layer of information, important for producing accurate and relevant responses.

I have extensive experience working in cross-functional teams where I collaborated closely with engineers, product managers, and designers. This collaboration is key to ensuring that all aspects of product quality are addressed, and I ensure that feedback flows freely among all team members to create effective solutions.

To stay updated on advancements in AI technology, I follow industry-leading publications, attend webinars, and participate in professional groups focused on AI. Networking with other professionals and engaging in ongoing learning opportunities is essential for keeping my skills and knowledge current in this rapidly evolving field.

What I enjoy most about working with AI in a quality assurance capacity is the challenge of problem-solving in real time and the opportunity to innovate continuously. Every update to the AI model is a chance to improve the user experience, and I find it rewarding to contribute significantly to a product that transforms how people interact with technology.

I evaluate user feedback by systematically tracking trends and specific issues reported by users. I categorize this feedback, conduct root cause analyses on recurring problems, and collaborate with developers to make targeted adjustments based on this information, using it as a foundation for driving improvements in the AI's outputs.