AI Research Lead
Role Overview
This senior-level AI Research Lead role involves setting the macro research direction across modalities, mentoring a team of researchers, and driving the development of SOTA Online LLMs (Sonar models) using supervised and reinforcement learning techniques. Day-to-day responsibilities include post-training LLMs, optimizing data and training pipelines, and collaborating with engineering and product teams to integrate models and align research with business objectives. The hire will have significant impact by advancing model capabilities, fostering team growth, and delivering cutting-edge query answering performance.
Perks & Benefits
The role is fully remote, offering flexibility in work location, with likely expectations for collaboration across time zones in a fast-paced startup environment. Career growth opportunities include leading strategic research, mentoring a team, and driving innovation in AI, supported by a collaborative culture that encourages knowledge sharing and professional development. Benefits may include typical tech perks like competitive compensation and resources for research, though not explicitly stated.
Full Job Description
Perplexity is seeking an exceptional AI Research Tech Lead to drive our research strategy and lead the development of our in-house Online LLMs, the Sonar models. In this leadership role, you will set the macro research direction across different modalities, mentor a team of researchers, and take advantage of our rich query/answer dataset to continue scaling our Sonar model performance and deliver the SOTA Online LLM experience to our users.
Responsibilities
Research Leadership & Strategy
Define and execute the 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 their technical and professional growth
Establish the long-term macro research direction across the team, including our direction across different modalities
Lead hiring and onboarding of new research talent
Create a collaborative environment that encourages knowledge sharing and innovation
Technical Excellence
Post-train SOTA 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 SOTA 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 our product
Partner with product teams to understand user needs and translate them into research priorities
Collaborate with data teams to leverage our unique query/answer dataset effectively
Communicate research progress and findings to stakeholders across the organization
Qualifications
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 at a premier academic intitution
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
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