Data Scientist (AI Data & LLM Specialist)
加入 Eclipse 的核心团队，我们正在建立一个人工智能代理的市场，将智能与现实世界任务联系起来，从数据收集和标签开始。我们寻找一名数据科学家来为下一代大语言模型 (LLM) 将我们的数据标记，处理和准备用于消费的方式奠定基础。你的工作将在转化原始数据集成成为有价值的，人工智能准备的数据集中至关重要。资格 ·作为数据科学家或机器学习工程师的经验，专注于数据质量和准备。· 强大的了解数据标签方法和与数据注释平台和工作流程的实践经验。· 展示了为培训和细节调整大型语言模型 (LLM) 的数据集的经验，包括对代码化，嵌入式和 NER 等技术的知识。·熟练掌握 Python 以及普通数据科学图书馆 （例如潘达斯，NumPy,Scikit-learn,spaCy, Hugging Face）. ·使用 API/SDK 来自动化数据注释和积极学习循环的经验。•优秀的沟通技能，具有针对技术和非技术观众创建明确文档的能力。责任 ·制定数据标签策略：设计和记录一个正式的数据注释策略，包括明确，可扩展和有效地标记我们的数据。定义并执行质量指标，包括分类注释者之间的协议。· 为 LLM 消费优化：研究，定义和原型开发我们数据集中的微调和培训 LLM 所需的最佳数据格式，结构和预处理步骤。· 数据质量分析：建立自动化的过程和指标来分析原料和标签数据的质量，为改善我们的数据收集和标签工作流程提供反。·与工程合作：与工程团队密切合作，以指导数据处理管道的实施并确保数据基础设施满足 ML 应用程序的需求。很好玩 · 有了音频数据处理和相关图书馆的经验。·熟悉数据注释平台和工具。·了解现代 MLOps 原则和实践。·与大型语言模型数据策划和加强从人类反 (RLHF) 管道的经验
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Join the core team at Eclipse, where we’re building an AI agent-first marketplace that connects intelligence with real-world tasks, starting with data collection and labeling. We are seeking a Data Scientist to establish the foundation for how our data is labeled, processed, and prepared for consumption by next-generation Large Language Models (LLMs). Your work will be critical in transforming our raw data collections into valuable, AI-ready datasets.
Qualifications
- Proven experience as a Data Scientist or Machine Learning Engineer with a focus on data quality and preparation.
- Strong understanding of data labeling methodologies and hands-on experience with data annotation platforms and workflows.
- Demonstrated experience preparing datasets for training and fine-tuning Large Language Models (LLMs), including knowledge of techniques like tokenization, embeddings, and NER.
- Proficiency in Python and common data science libraries (e.g., Pandas, NumPy, Scikit-learn, spaCy, Hugging Face).
- Experience using APIs/SDKs to automate data annotation and active learning loops.
- Excellent communication skills, with an ability to create clear documentation for technical and non-technical audiences.
Responsibilities
- Develop Data Labeling Strategies: Design and document a formal data annotation strategy, including clear, scalable, and efficient guidelines for labeling our data. Define and enforce quality metrics, including inter-annotator agreement.
- Optimize for LLM Consumption: Research, define, and prototype the optimal data formats, structures, and pre-processing steps required for fine-tuning and training LLMs on our datasets.
- Data Quality Analysis: Establish automated processes and metrics to analyze the quality of both raw and labeled data, providing feedback to improve our data collection and labeling workflows.
- Collaborate with Engineering: Work closely with the engineering team to guide the implementation of data processing pipelines and ensure the data infrastructure meets the needs of ML applications.
Nice-to-Haves
- Experience with audio data processing and relevant libraries.
- Familiarity with data annotation platforms and tools.
- Knowledge of modern MLOps principles and practices.
- Experience with large language model data curation and Reinforcement Learning from Human Feedback (RLHF) pipelines.
Join the Eclipse team!
Eclipse is building the fastest Ethereum Layer 2, powered by the Solana VM. Our general-purpose L2 combines the best of the modular stack without sacrificing UX or fragmenting liquidity. On top of this foundation, we’re building apps in-house and iterating quickly to find breakout consumer and AI experiences. We’re backed by top investors including Polychain, Tribe Capital, Placeholder, and DBA.
- Opportunity. We believe blockchains should be fast AND highly usable. You’ll do high-impact work to enhance Ethereum’s scalability, shaping the future of crypto
- Flexibility. We collaborate synchronously and asynchronously, across weekly all-hands meetings, Slack messaging, and quarterly in-person meetups
- Team. Our founding team has experience launching and scaling blue-chip projects such as dYdX, Uniswap, and zkSync. We’re backed by leading funds and leaders including Polychain, Tribe, Placeholder, DBA, Mustafa Al-Bassam, Tarun Chitra, Meltem Demirors, and others
- Culture. As an early member of our team, you’ll have a unique opportunity to help shape our culture. We value intellectual honesty, bias towards action, and believe every member plays a key role in achieving our ambitious goals
- Compensation. You’ll receive a competitive salary + equity + benefits package.
Eclipse Laboratories is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, age, disability, genetic information, veteran status, or any other status protected by applicable laws or regulations. All employment decisions are based on qualifications, merit, and business need.
Originally posted on Himalayas