哔哩哔哩游戏算法实习生
实习兼职技术类地点:上海状态:招聘♡ 收藏
工作描述
工作职责: 1、营销推荐:参与游戏营销推荐及用户增长算法研发,包括转化率预估(CVR)、用户价值预测(LTV)、因果推断、Uplift Modeling、运筹优化、个性化推荐等方向,提升用户转化效率及营销效果; 2、广告投放:参与游戏广告投放与商业化算法研发,包括 pLTV/ROI 预测、出价预测(Bidding)、转化回传预测、归因建模、投放策略优化、素材理解与优化等方向,提升广告投放效率与 ROI; 3、模型训练:参与 LAM 行为序列基座模型及游戏领域大模型建设,包括用户行为序列建模、Transformer、Embedding、预训练、SFT、LoRA、蒸馏、RLHF、DPO、GRPO 等训练及后训练技术; 4、大模型翻译:参与游戏出海多语言翻译及本地化算法研发,包括机器翻译(MT)、多语言大模型、RAG、SFT、强化学习、翻译质量评估(TQE)、LLM as Judge 等方向,探索大模型在游戏本地化生产及质量控制中的应用; 5、大模型对话:参与游戏内智能对话、AI NPC、游戏智能助手等算法研发,包括 LLM、RAG、知识库、Tool Calling、Memory、Multi-Agent、MCP 等技术,探索大模型及智能…
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包括英文材料
算法+
https://roadmap.sh/datastructures-and-algorithms
Step by step guide to learn Data Structures and Algorithms in 2025
https://www.hellointerview.com/learn/code
A visual guide to the most important patterns and approaches for the coding interview.
https://www.w3schools.com/dsa/
因果推断+
https://web.stanford.edu/~swager/causal_inf_book.pdf
How best to understand and characterize causality is an age-old question in philosophy.
运筹优化+
https://medium.com/gousto-engineering-techbrunch/an-introduction-to-operations-research-5a9e898b6c60
Operations research (OR) is a scientific approach to determining the optimal solution to a defined business problem.
大模型+
https://www.youtube.com/watch?v=xZDB1naRUlk
You will build projects with LLMs that will enable you to create dynamic interfaces, interact with vast amounts of text data, and even empower LLMs with the capability to browse the internet for research papers.
https://www.youtube.com/watch?v=zjkBMFhNj_g
Transformer+
https://huggingface.co/learn/llm-course/en/chapter1/4
Breaking down how Large Language Models work, visualizing how data flows through.
https://poloclub.github.io/transformer-explainer/
An interactive visualization tool showing you how transformer models work in large language models (LLM) like GPT.
https://www.youtube.com/watch?v=wjZofJX0v4M
Breaking down how Large Language Models work, visualizing how data flows through.
SFT+
https://cameronrwolfe.substack.com/p/understanding-and-using-supervised
Understanding how SFT works from the idea to a working implementation...
RLHF+
[英文] What is RLHF?
https://aws.amazon.com/what-is/reinforcement-learning-from-human-feedback/
Reinforcement learning from human feedback (RLHF) is a machine learning (ML) technique that uses human feedback to optimize ML models to self-learn more efficiently.
https://www.ibm.com/think/topics/rlhf
Reinforcement learning from human feedback (RLHF) is a machine learning technique in which a “reward model” is trained with direct human feedback, then used to optimize the performance of an artificial intelligence agent through reinforcement learning.
GRPO+
https://cameronrwolfe.substack.com/p/grpo
Most early work on RL for LLMs used Proximal Policy Optimization (PPO) as the default RL optimizer, but recent reasoning research relies upon Group Relative Policy Optimization (GRPO).
RAG+
https://www.youtube.com/watch?v=sVcwVQRHIc8
Learn how to implement RAG (Retrieval Augmented Generation) from scratch, straight from a LangChain software engineer.
强化学习+
https://cloud.google.com/discover/what-is-reinforcement-learning?hl=en
Reinforcement learning (RL) is a type of machine learning where an "agent" learns optimal behavior through interaction with its environment.
https://huggingface.co/learn/deep-rl-course/unit0/introduction
This course will teach you about Deep Reinforcement Learning from beginner to expert. It’s completely free and open-source!
https://www.kaggle.com/learn/intro-to-game-ai-and-reinforcement-learning
Build your own video game bots, using classic and cutting-edge algorithms.
AI agent+
https://www.ibm.com/think/ai-agents
Your one-stop resource for gaining in-depth knowledge and hands-on applications of AI agents.
MCP+
https://www.youtube.com/watch?v=eur8dUO9mvE
Unlock the secrets of MCP! 🚀 Dive into the world of Model Context Protocol and learn how to seamlessly connect AI agents to databases, APIs, and more. Roy Derks breaks down its components, from hosts to servers, and showcases real-world applications. Gain the knowledge to revolutionize your AI projects!
https://www.youtube.com/watch?v=L94WBLL0KjY
Let's talk about MCP or the Model Context Protocol.
智能体+
https://learn.microsoft.com/en-us/shows/ai-agents-for-beginners/
In this 10-lesson course we take you from concept to code while covering the fundamentals of building AI agents.
https://www.ibm.com/think/ai-agents
Your one-stop resource for gaining in-depth knowledge and hands-on applications of AI agents.
特征工程+
https://www.ibm.com/think/topics/feature-engineering
Feature engineering preprocesses raw data into a machine-readable format. It optimizes ML model performance by transforming and selecting relevant features.
https://www.kaggle.com/learn/feature-engineering
Better features make better models. Discover how to get the most out of your data.
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