Generative AI Engineer - job 1 of 2

As a Generative AI Engineer at our company, you'll be responsible for leading the development of generative AI solutions. This includes strategic planning, technical execution, and creating customer-facing chat experiences integrated into our platforms. You'll need to deploy large language models, fine-tune them to improve our applications, and ensure the scalability of backend systems.

To qualify for the Generative AI Engineer role at our company, candidates should have at least 1 year of experience developing end-to-end foundational LLM models and 4 years of experience as a backend developer with a strong emphasis on Python. A good understanding of classical deep learning models such as CNN, RNN, and LSTM, along with experience deploying and fine-tuning LLMs, is essential.

The Generative AI Engineer position offers a great hybrid work schedule. You will work in the office from Tuesday to Thursday, allowing for face-to-face collaboration with your team, while you can enjoy the flexibility of remote work on Mondays and Fridays. This setup promotes a healthy work-life balance while maintaining productivity.

As a Generative AI Engineer at our company, you'll enjoy a competitive benefits package including a 12-15% bonus based on performance, stock options, unlimited PTO, a 401k match, and full coverage for medical, dental, and vision insurance. We prioritize the well-being of our team members and their families!

While prior experience in gaming development is a plus, it is not strictly necessary for the Generative AI Engineer position. The key requirements are experience with generative AI and backend development. If you have a passion for gaming and technology, your transferable skills will be valued in our innovative environment.

In your response, highlight specific projects where you developed, deployed, or integrated large language models into applications. Discuss the technologies and methodologies you used, as well as the impact of your work on user engagement or application performance.

Discuss your approach to fine-tuning models, including your understanding of the training data selection process, hyperparameter tuning, and any frameworks or tools you’ve utilized. Provide examples of models you've worked on and the outcomes achieved through your fine-tuning efforts.

Explain your techniques for scaling backend systems, such as implementing load balancers, optimizing database queries, or leveraging cloud services. Use specific examples to illustrate how your strategies have successfully improved system performance or handled increased loads.

Choose a relevant example where you encountered a technical challenge in AI development. Explain the problem, the steps you took to resolve it, and what you learned from the experience. This showcases your problem-solving skills and adaptability.

Discuss the deep learning algorithms you’re familiar with, such as CNN, RNN, or LSTM, and how you've applied them in real-world projects. Highlight specific applications like image recognition or natural language processing to illustrate your experience.

Talk about your commitment to continuous learning, including attending conferences, participating in online courses, or following relevant journals and platforms. This demonstrates your passion for the field and your dedication to professional growth.

Outline the key steps in your workflow, starting from the initial concept and data collection to model development, testing, and deployment. Providing a structured answer helps interviewers understand your project management skills.

Share specific examples of AI features you have built, such as chatbots or recommendation systems. Highlight their impact on user experience and any metrics that demonstrate success, showcasing your ability to create valuable customer-facing applications.

Describe your experience in collaborating with cross-functional teams, such as product management or design. Talk about your communication style and how you ensure alignment on project goals, which is essential for a role like the Generative AI Engineer.

Express your enthusiasm for the company's mission and culture. Relate your values to those of the organization and highlight how your skills align with the role. This shows you’ve done your research and are genuinely interested in being part of the team.