Member of Technical Staff (AI Researcher)
San Francisco • FullTime
Posted 19d ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
On-site
Employment Type
FullTime
Categories
AI Research Engineer
About the job
Perplexity is seeking top-tier AI Research Scientists and Engineers to advance our AI products and capabilities, focusing on building the future of AI-powered search and agent experiences. You will contribute to SOTA experiences that handle hundreds of millions of queries and continue to scale rapidly. Depending on your interests and expertise, you can join one of three specialized teams: the Core Research Team focusing on foundational models, the Agent Products Team fine-tuning models for agent and product experiences, or the Comet Agent Team dedicated to developing and enhancing the Comet Agent product.
Responsibilities
- Post-train SOTA LLMs using supervised and reinforcement learning techniques (SFT/DPO/GRPO).
- Leverage query/answer datasets to scale model performance across Sonar, Deep Research, Comet, and Search products.
- Stay current with the latest LLM research, particularly in model training, optimization, and personalization.
- Implement preference optimization and personalization capabilities to enhance user experience.
- Invent in-house improvements and optimizations for SOTA models.
- Translate research ideas into algorithms and run experiments to launch new models.
- Own full-stack data, training, and evaluation pipelines for model development.
- Build robust training frameworks (on top of Megatron/PyTorch) for post-training LLMs.
- Implement infrastructure and components for cutting-edge model training at scale.
- Integrate models seamlessly into the product ecosystem.
- Collaborate with engineering teams to integrate models into Perplexity's product suite.
- Ensure cohesive AI experiences across the platform through cross-team collaboration.
- Partner with product teams to understand user needs and translate them into model improvements.
Requirements
- Proven experience with large-scale LLMs and Deep Learning systems.
- Strong programming skills in Python/PyTorch; versatility is a plus.
- Experience with post-training techniques and reinforcement learning.
- Self-starter with a willingness to take ownership of tasks.
- Passion for tackling challenging problems.
- Minimum 2-6 years of experience on relevant projects.
- Experience in post-training LLMs with SFT/DPO/GRPO (nice-to-have).
- C++/CUDA programming skills (nice-to-have).
- Experience building LLM training frameworks (nice-to-have).
- Academic publications and research impact (nice-to-have).
- Experience with agent systems and multi-step reasoning (nice-to-have).
- Background in personalization and preference learning (nice-to-have).