LLM Algorithm Engineer

3 weeks ago

Singapur, Singapore CoinMarketCap Full time

Join to apply for the LLM Algorithm Engineer role at CoinMarketCap .

  • 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 evaluation pipelines for alignment, factuality, grounding, and hallucinations.
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.
  • Proficiency in Python and relevant machine learning frameworks (e.g., PyTorch, TensorFlow).
  • Strong understanding of distributed systems and high-performance computing.
  • Experience with model deployment and inference optimization on vLLM or Triton clusters.
  • Knowledge of JSON-schema and API development.
Seniority level
  • Not Applicable
Employment type
  • Full-time
Job function
  • Engineering and Information Technology
  • Industries: Information Services

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