About the company
CoinMarketCap is the world’s most trusted and accurate source of data for cryptocurrencies. Used by millions of individuals, organizations, and exchanges, CoinMarketCap brings the most up-to-date market capitalizations, pricing, and cryptocurrency information to our users. Pulling data from multiple exchanges and combining our robust research allows us to provide the most realistic representation of each cryptocurrency. As we grow, we will continue to provide access to our data wherever, whenever, and however is most helpful to our users.
Job Summary
Job Responsibilities：
📍 Advanced post-training of large language models (e.g. SFT, RLHF/RLAIF, continual pretraining). 📍 Aligning models for reliable JSON-schema function calls and external tool usage. 📍 Design, deploy, and operate Model Context Protocol (MCP) servers that handle checkpoint routing, manage context windows, and enforce safety gates. 📍Experience in distributed training and inference with DeepSpeed/FSDP, LoRA/QLoRA, mixed precision, and performance tuning on vLLM or Triton clusters. 📍 Build offline and live eval pipelines for alignment, factuality, grounding, and hallucinations.
Qualifications
📍 Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. 📍 3+ years of experience in developing and optimizing large language models. 📍Proven track record in implementing advanced post-training techniques (SFT, RLHF, RLAIF, continual pretraining). 📍Hands-on experience with distributed training frameworks (DeepSpeed, FSDP) and optimization techniques (LoRA, QLoRA, mixed precision). 📍Familiarity with model alignment, JSON-schema function calls, and external tool integration. 📍Experience in building and maintaining evaluation pipelines for model performance assessment.
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