Algorithm Engineer

About Us

rednote Algorithm Team works at the intersection of recommendation, search, advertising, content understanding, and large language models. Our work spans community content distribution, e-commerce, monetization, and content safety — all in service of one goal: using algorithms to connect people with content and products, and building a community that feels human.

Roles & Responsibilities

We're hiring across the following tracks:

• Recommendation / Search / Advertising Algorithms — Core algorithm R&D across the full ranking pipeline: retrieval, pre-ranking, ranking, and re-ranking for feeds, search, and ads.
• Large Models & AIGC — Apply and advance LLMs and multimodal models in recommendation, search, ads, and content generation. Work spans pre-training, post-training (SFT / RLHF / DPO), RAG, and Agent frameworks.
• Content Understanding & Multimodal AI — Build multimodal understanding across image, text, video, and audio. Develop capabilities in content quality assessment, semantic representation, and cross-modal retrieval to power recommendation and safety systems.
• User Understanding & Growth — Develop foundational algorithms for user profiling, behavior sequence modeling, and interest representation to enable precise recommendation, intelligent marketing, and user growth.
• Trust & Safety — Leverage NLP, multimodal, and LLM techniques to detect policy-violating content and malicious behavior, keeping the platform ecosystem healthy.
• Frontier Research & Innovation — Track and rapidly productionize cutting-edge advances (generative recommendation, One Model architectures, Scaling Laws, etc.) to drive measurable business impact.

Qualifications

• Bachelor's degree or above in Computer Science, Software Engineering, Mathematics, Statistics, or a related field.
• Strong foundations in machine learning and deep learning; solid experience in at least one of: recommendation systems, search engines, computational advertising, NLP, or CV.
• Strong engineering skills; proficiency in Python, Java, or C++; hands-on experience with PyTorch or TensorFlow.
• Publications at top-tier venues (KDD, NeurIPS, ICML, CVPR, ACL, RecSys, ICLR, etc.) are a plus.
• Competitive programming or data science competition experience (ACM ICPC, Kaggle, etc.) is a plus.
• Self-motivated, clear communicator, strong analytical thinker — able to quickly diagnose problems and drive solutions in complex, fast-moving environments.

What We're Looking For

• You're genuinely excited about technology and want to sharpen algorithms on real, large-scale data.
• You can distill complex business problems into clean technical problem statements and drive them to production.
• You're curious — actively following developments in LLMs, generative AI, and what's coming next.