The Applied AI Engineer at Salient is tasked with developing and deploying advanced multimodal AI systems, focusing primarily on voice interactions. This involves creating systems that work seamlessly at large scale while ensuring safety and compliance with financial regulations. Key responsibilities include implementing safety frameworks for LLM interactions, building monitoring systems for model behaviors, and collaborating with product and engineering teams to balance rapid deployment with scalability.

Candidates applying for the Applied AI Engineer position at Salient should have at least three years of experience working directly with large language models (LLMs) or voice AI technologies. A deep understanding of modern LLM techniques like retrieval-augmented generation (RAG), fine-tuning, and prompt engineering is essential, alongside experience in Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) technologies. Strong skills in machine learning systems design and effective cross-functional communication are also required.

Salient prioritizes compliance with financial regulations by implementing robust safety and alignment frameworks in its AI systems. As an Applied AI Engineer, one of your roles will be to ensure that the AI technologies deployed not only meet safety standards but also adhere to the specific compliance requirements of the financial industry. This involves continuous monitoring and adjusting of systems to align with changing regulatory standards.

At Salient, the company culture revolves around innovation, collaboration, and a shared mission to transform the auto lending space. The environment is dynamic, encouraging team members to push boundaries in multimodal AI while ensuring individual and team growth. The company's commitment to safety and compliance also fosters a culture of responsibility, where everyone has a role in maintaining high standards of operation.

Salient offers tremendous growth opportunities for Applied AI Engineers, especially given its rapid expansion since its launch in September 2023. As the company continues to scale and innovate in the AI domain, you will have ample opportunities to take on new responsibilities, work on exciting projects, and develop your skill set in various aspects of multimodal AI and machine learning in a supportive environment.

Be prepared to discuss specific projects where you've implemented or worked directly with large language models. Highlight your knowledge of techniques like fine-tuning, prompt engineering, or retrieval-augmented generation and how they applied to real-world scenarios.

Focus on safety frameworks that uphold ethical standards in AI. Discuss any experience you have with compliance regulations in financial services, detailing how you ensured AI interactions were safe and aligned with user expectations.

Explain your approach to building scalable monitoring systems for AI models. Share examples of how you've previously detected and responded to unexpected model behavior, along with lessons learned from those experiences.

Talk about a specific project where you faced challenges in developing voice AI solutions. Discuss how you overcame those obstacles, focusing on technical details and your contributions as part of a team.

Discuss your experience with balancing feature deployment and system scalability. You can include strategies you’ve employed to enhance performance without compromising on system architecture, emphasizing design patterns and methodologies.

Mention your experiences collaborating with product and engineering teams. Emphasize tools and practices you use to maintain clarity in communication and ensure everyone is aligned on project goals.

Share your insights into the latest trends in multimodal AI, especially regarding how these trends could impact financial services. Discuss innovations and potential applications that you find particularly interesting.

Provide examples of AI systems you’ve worked on that required compliance with financial regulations. Detail your role in ensuring these systems were compliant and how you navigated regulatory challenges.

Reflect on your approach to keeping up with the rapidly evolving landscape of AI technologies. Discuss any relevant courses, conferences, or resources that have helped you grow your skill set.

Talk about strategies you employ to manage priorities effectively when working under pressure. Highlight tools you use for project management and any methods that help you remain focused and productive.