AI Engineer

As an AI Engineer at Humata, your main responsibilities will include developing and implementing innovative architectures for document search and knowledge retrieval. You'll work on cutting-edge methods such as image-based Retrieval-Augmented Generation (RAG) and machine learning-based re-ranking. Additionally, you'll take ownership of critical projects as part of our cognitive architecture strategy, ensuring the delivery of impactful solutions.

To qualify for the AI Engineer position at Humata, candidates must have a minimum of 5 years of software engineering experience, proven production experience with large language models (LLMs), and a strong background in Retrieval-Augmented Generation. Proficiency in languages such as Typescript and Python is essential, as well as knowledge of search engines like ElasticSearch and experience with cloud services.

In addition to the required qualifications for the AI Engineer position at Humata, having experience in AI/ML research, particularly in training and fine-tuning LLMs, can greatly enhance your application. Familiarity with Node.js development is also beneficial, as well as strong collaboration skills, an ownership mentality, and the ability to thrive in a startup environment.

As an AI Engineer at Humata, you will work on transforming the landscape of document search and knowledge retrieval. This includes pioneering projects that implement novel methodologies like machine learning-based re-ranking and image-based RAG. Your work will have a significant impact on our cognitive architecture, and you'll have the opportunity to innovate and influence the direction of our technology.

Working at a startup like Humata is appealing for an AI Engineer because it provides a unique opportunity to make a significant impact in a fast-paced and innovative environment. You'll have the chance to take ownership of projects, work with cutting-edge technology in AI, and contribute to shaping the future of how users interact with information. This role offers both creative freedom and a collaborative culture.

In your answer, describe specific projects where you utilized large language models, detailing the techniques you applied and the outcomes achieved. Highlight how you fine-tuned LLMs for accuracy and their integration within retrieval systems to enhance document search.

Discuss methodologies you've successfully implemented in RAG, including both traditional and innovative approaches. Use examples to illustrate how you improved search outcomes or information retrieval through these techniques.

Share a specific challenge related to an AI project, focusing on the steps you took to identify the problem, your problem-solving strategies, and the final results of your efforts. This showcases your resilience and ability to think critically under pressure.

In your answer, mention specific resources such as academic journals, online courses, webinars, or professional networks. Highlight your commitment to lifelong learning and how you implement new knowledge into your work.

Explain your thought process regarding user experience, efficiency, and accuracy in designing search systems. Discuss your approach to implementing user feedback and continuous improvement in your designs.

Share a project example that required collaboration, detailing how you communicated with team members, coordinated tasks, and integrated feedback. Emphasize the project outcome and the importance of teamwork in achieving success.

Discuss your hands-on experience with cloud platforms, including specific projects where you utilized AWS or GCP services. Explain how you leveraged these platforms to improve project scalability and efficiency.

Explain your systematic approach to debugging, detailing the tools and methodologies you use. Emphasize the importance of analytical thinking and documenting your process for resolving issues.

Describe a situation where you had to quickly adapt to new technology or methodologies. Focus on the strategies you employed to remain agile and how you successfully integrated new approaches into your work.

Articulate your excitement about the potential for innovation in AI, the thrill of being part of a startup, and the opportunity to shape product development. Discuss how this aligns with your professional goals and aspirations.