AI Research Lead

Details

Perplexity is seeking an exceptional AI Research Tech Lead to drive research strategy and lead development of in-house online LLMs (the Sonar models). In this leadership role you will set macro research direction across modalities, mentor a team of researchers, and use Perplexity's query/answer dataset to scale Sonar model performance and deliver a state-of-the-art online LLM experience.

Responsibilities

Research Leadership & Strategy

• Define and execute macro research direction across multiple modalities, including post-training LLMs for agent trajectories and future mid-training initiatives.
• Lead strategic research planning and roadmap development to advance Sonar model capabilities.
• Drive innovation in supervised and reinforcement learning techniques for query answering.
• Collaborate with leadership to align research priorities with product and business objectives.

Team Development & Mentorship

• Coach and mentor a team of AI research scientists and engineers, fostering technical and professional growth.
• Establish long-term macro research direction across the team and modalities.
• Lead hiring and onboarding of new research talent.
• Create a collaborative environment that encourages knowledge sharing and innovation.

Technical Excellence

• Post-train state-of-the-art LLMs on query answering using cutting-edge supervised and reinforcement learning techniques.
• Own and optimize the full stack data, training, and evaluation pipelines required for LLM post-training.
• Deliver Sonar models that provide state-of-the-art query answering performance.
• Drive research into agent trajectories and multi-modal capabilities.
• Lead the technical roadmap for eventual mid-training investments.

Cross-Functional Collaboration

• Work closely with engineering teams to integrate Sonar models into product.
• Partner with product teams to understand user needs and translate them into research priorities.
• Collaborate with data teams to leverage the unique query/answer dataset effectively.
• Communicate research progress and findings to stakeholders across the organization.

Requirements

Required

• Minimum of 5 years of experience working on relevant AI/ML projects, with 3+ years in a technical leadership role.
• Proven track record of leading and mentoring technical and research teams.
• A Computer Science graduate degree from a premier academic institution.
• Deep expertise with large-scale LLMs and deep learning systems.
• Strong programming skills with versatility across multiple languages and frameworks.
• Demonstrated ability to set technical vision and drive execution.
• Experience with pre-training and post-training techniques (self-supervised learning along with SFT/DPO/GRPO/PPO).
• Self-starter with exceptional ownership mentality and ability to work in ambiguous environments.
• Passion for solving challenging problems and pushing the boundaries of AI research.

Nice-to-have

• PhD in Machine Learning, Computer Science, or related areas.
• Experience with agent-based AI systems and multi-modal model development.
• Background in mid-training or pre-training of large language models.
• Publications in top-tier AI/ML conferences.
• Experience in fast-paced startup environments.
• Track record of translating research into production systems.

Compensation & Benefits

• Cash compensation range: $370,000 - $460,000 per year.
• Final offers are determined by multiple factors, including experience and expertise, and may vary from the amounts listed above.
• Equity may be part of the total compensation package.
• Benefits include comprehensive health, dental, and vision insurance for you and your dependents, and a 401(k) plan.