The Rundown AI, Inc.
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.
ResponsibilitiesResearch 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 QualificationsRequired
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 Compensation & Benefits Our cash compensation range for this role is $370,000 - $460,000. Final offer amounts are determined by multiple factors, including experience and expertise, and may vary from the amounts listed above.
Have you got the right qualifications and skills for this job Find out below, and hit apply to be considered.
Equity: In addition to the base salary, equitymay be partof the total compensation package. Benefits: Comprehensive health, dental, and vision insurance for you and your dependents. Includes a 401(k) plan.
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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 QualificationsRequired
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 Compensation & Benefits Our cash compensation range for this role is $370,000 - $460,000. Final offer amounts are determined by multiple factors, including experience and expertise, and may vary from the amounts listed above.
Have you got the right qualifications and skills for this job Find out below, and hit apply to be considered.
Equity: In addition to the base salary, equitymay be partof the total compensation package. Benefits: Comprehensive health, dental, and vision insurance for you and your dependents. Includes a 401(k) plan.
#J-18808-Ljbffr