LLM Engineer

As an LLM Engineer at Brainbay, you will lead the development and deployment of large language model applications tailored for the real estate sector. Your primary responsibilities include designing AI-driven tools to improve operational efficiency for NVM members, collaborating with cross-functional teams, and ensuring that the AI agent meets industry standards. You will also engage in prompt engineering and work with existing data infrastructures to implement retrieval-augmented generation techniques.

To be considered for the LLM Engineer position at Brainbay, candidates must have proven experience in LLM application development and cloud deployment (preferably on AWS). A solid understanding of Retrieval-Augmented Generation and prompt engineering techniques is essential, along with proficiency in Python, popular machine learning libraries like TensorFlow and PyTorch, SQL, and Git. Familiarity with CI/CD pipelines and ML Ops tools will also enhance your application, along with fluency in English and Dutch.

The work environment for an LLM Engineer at Brainbay is designed to foster innovation and collaboration. We offer hybrid work options, allowing flexibility between remote and in-office work, to create a balance that boosts productivity. Our office in Utrecht is a vibrant space where you can brainstorm ideas with fellow experts. You'll also find that we prioritize professional development, encouraging engineers to continuously expand their skill sets.

When you join Brainbay as an LLM Engineer, you can expect a competitive salary ranging from €65,000 to €80,000 annually, along with a 13th-month bonus. We also provide an extensive benefits package that includes up to 37 vacation days, a robust pension plan with only a 1% employee contribution, and support for your home office setup. Additionally, you’ll have access to a €1,500 annual training budget to enhance your skills and career growth.

Yes, candidates applying for the LLM Engineer position at Brainbay must currently reside in the Netherlands. This requirement allows for seamless collaboration with team members and ensures that all communication is effective, especially since fluency in both Dutch and English is a fundamental part of our working environment.

When answering this question, highlight specific projects you've worked on involving large language models. Discuss the types of applications you've developed, the challenges faced, and how you overcame them. Ensure to mention any results or impact these applications had, particularly if they improved efficiency or accuracy in a given task.

To effectively respond, explain the methodologies you use for prompt engineering, including testing and iteration processes. Provide examples of how you've fine-tuned prompts to yield better results in LLM applications and articulate your understanding of context and intent in crafting prompts.

When addressing this question, mention specific resources you utilize, such as academic journals, reputable blogs, or industry conferences. Highlight any online courses or training you've undertaken to improve your skills, showing your commitment to continuous learning in AI and machine learning.

Focus on providing concrete examples of cloud deployment projects you've led or participated in, particularly emphasizing your familiarity with AWS. Discuss the processes involved, including any challenges and how you ensured the reliability and scalability of AI applications in the cloud.

Detail the specific tools and libraries you've worked with, including TensorFlow, PyTorch, and Hugging Face. Illustrate how you have applied these technologies to your projects, and also mention your experience with APIs and data pipelines, which are vital for integrating AI solutions.

Provide a specific scenario where you collected and analyzed data to inform a decision in your previous work. Highlight how you interpreted the results and what actions were taken based on your insights. This showcases your analytical skills and ability to leverage data effectively.

Discuss your strategies for effective communication, using easy-to-understand language to explain technical concepts. Share an example of a successful collaboration that required you to bridge the gap between technical and non-technical team members, demonstrating your teamwork and communication skills.

Articulate your awareness of the nuances in the real estate industry, such as data privacy, bias in AI, and the need for transparency. Discuss how you intend to address these challenges in your role as an LLM Engineer and your approach to ethical considerations in AI development.

Explain your systematic approach to testing AI models before deployment, including validation, performance metrics, and user feedback. Discuss any CI/CD practices you implement to ensure smooth deployment and continuous integration of updates in your AI applications.

To answer this question, share your enthusiasm for Brainbay's mission and how it aligns with your career goals. Discuss your admiration for their innovative approach in real estate and your eagerness to contribute to the development of AI solutions that have a direct impact on the industry.