Research Engineering Manager - Model Training

Perplexity is seeking a Research Engineering Manager to lead the team of all-star AI researchers and engineers responsible for developing the models that drive our products. Our team has developed some of the most advanced models for agentic research, query understanding, and other domains that require accuracy and depth. As we expand our userbase and portfolio of product surfaces, our in-house models are increasingly critical to providing a premium, high-taste experience for the world’s most sophisticated users.

You will dive into our rich datasets of conversational and agentic queries, leveraging cutting‑edge training techniques to scale AI model performance. Through hands-on technical and organizational leadership, you will empower your team to develop SotA models for the use cases that matter most to our business and our users.

RESPONSIBILITIES

- Lead a team of researchers and engineers focused on training SotA models for Perplexity-relevant use cases, leveraging the latest supervised and reinforcement learning techniques.

- Drive research and engineering efforts to develop production models through advanced model training and alignment techniques, including RL, SFT, and other approaches.

- Become deeply familiar with the team’s technical stack, leading from the front through hands-on technical contributions.

- Own the data, training, and eval pipelines required to train and continuously improve LLM models.

- Design and iterate on model training and finetuning algorithms (e.g., preference‑based methods, reinforcement learning from human or AI feedback) through an approach that balances scientific rigor and iteration velocity.

- Design evaluations and improve the production model training pipeline to reliably deliver models that lie on the Pareto frontier of speed and quality.

- Work closely with engineering teams to integrate in-house models into our product and rapidly iterate based on real‑world usage.

- Manage day‑to‑day execution, proje...