Principal Engineer, Machine Learning, SMAI

The role involves architecting and executing large-scale custom model training and fine-tuning jobs on multi-node GPU clusters, while also designing and developing autonomous AI Agents for complex manufacturing workflow automation. Responsibilities include optimizing training throughput, implementing Agentic frameworks, and building/maintaining data/solution pipelines feeding these AI/ML solutions. Candidates must possess deep expertise in GPU architecture, distributed training techniques (DDP, FSDP), and proficiency in fine-tuning LLMs using PEFT methods, along with experience developing GenAI applications and AI Agents using frameworks like LangChain. Minimum qualifications require 9+ years in scalable ETL pipelines and big data processing, strong Python skills, and familiarity with ML frameworks like PyTorch.