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 techn...