Data Scientist (AI Data & LLM Specialist)
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.
Requirements
- 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.
Preferred Qualifications
- 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.
Why Join
- 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.
How to Apply
Apply through the official job page.
