AI Engineer

As an AI Engineer at Relevance AI, your primary responsibilities will include writing clean and efficient code, maintaining a Python SDK to streamline AI agent development, and designing large language models to enhance our agent capabilities. You will also engage in multi-agent system frameworks, analyze product data, and work on Retrieval-Augmented Generation pipelines.

To qualify for the AI Engineer role at Relevance AI, you should have at least 2 years of experience in software development or AI engineering, strong proficiency in Python (and ideally Typescript), and be knowledgeable about agent platforms like Llangchain and LlamaIndex. Experience with RAG and LLMs is highly desirable.

The work environment for an AI Engineer at Relevance AI is dynamic and collaborative. You'll work in a hybrid model, spending three days in the Sydney office, where you'll interact with a talented team dedicated to pushing the boundaries of AI technology. The culture encourages innovation and the sharing of ideas to drive progress.

As an AI Engineer at Relevance AI, you'll primarily work with Python and Typescript. You'll also engage with various technologies related to AI and machine learning, specifically large language models and microservices architecture. Familiarity with RESTful APIs and agent platforms such as Llangchain will be essential.

Relevance AI is committed to professional growth and offers numerous opportunities for career development. As an early team member, you can shape our workplace culture and benefit from competitive salaries, unparalleled professional growth, and high-trust environment that empowers you to share your innovative ideas.

When tackling this question, focus on specific projects you've worked on, highlighting your role, the technologies you used, and the outcomes. Mention any challenges you encountered and how you overcame them, showcasing your problem-solving skills.

Discuss your proficiency in Python and Typescript as they relate to AI development. Provide examples of how you've utilized these languages in your projects, emphasizing their role in streamlining development processes and enhancing model performance.

Share the resources you rely on, such as industry blogs, research papers, conferences, or online courses. Highlight your passion for continuous learning and how you've applied new knowledge to projects in the past.

Provide a detailed account of your experience with Large Language Models (LLMs), including any specific frameworks or platforms you’ve used. Discuss how you trained and fine-tuned these models and their impact on the projects you worked on.

Detail your understanding of multi-agent systems and their relevance in AI. Discuss any projects where you've applied this knowledge, emphasizing the design, functionality, and ultimate benefits of implementing a multi-agent approach.

Reflect on specific challenges you've encountered in AI projects, such as data limitations or algorithmic issues. Describe the strategies you employed to address these challenges, demonstrating your resilience and resourcefulness.

Emphasize your coding practices, such as following industry standards, utilizing design patterns, and conducting code reviews. Explain how these approaches contribute to maintainability and scalability in software projects.

Discuss techniques you've used to optimize AI model performance, such as hyperparameter tuning or leveraging powerful computing resources. Give examples of how these strategies have enhanced model efficiency in your past work.

Talk about your experiences collaborating with cross-functional teams, highlighting your communication skills and ability to integrate diverse perspectives. Share how you contribute to a positive team dynamic and project success.

Articulate your passion for AI and why Relevance AI’s mission resonates with you. Mention specific aspects of the company culture and the innovative projects that excite you, reinforcing your enthusiasm for the role.