Principal Applied Scientist

What you'll do

• Design and implement ranking models using deep learning and large language models for content recommendation.
• Architect next-generation ranking systems for large-scale scenarios, including generative recommendations and agentic feeds.
• Lead the design of efficient ML/DL pipelines with feature engineering, model training, evaluation, and online inference.
• Drive innovation in model architectures like LLM-enhanced ranking and reinforcement learning.
• Mentor junior team members to foster a culture of technical excellence and knowledge sharing.

What we're looking for

• 8+ years of experience in applied science or deep learning with a track record of delivering production ML systems at scale.
• Expertise in recommendation systems, ranking models, search relevance, and personalization techniques.
• Proficiency in modern ML frameworks like PyTorch and TensorFlow, and cloud-scale infrastructure.
• Demonstrated ability to lead cross-functional initiatives and influence technical direction across teams.
• Solid architectural skills for designing large-scale ML systems and distributed pipelines.
• Experience with LLM-based ranking, agentic AI, or generative AI applied to recommendation systems.