LLM Engineer

Overview

We are hiring an LLM Engineer to build the infrastructure that makes language models reliable, observable, and cost-efficient in production. You will own the model-serving layer, fine-tuning pipelines, and evaluation frameworks.

Responsibilities

• Design and deploy model-serving infrastructure with low-latency inference and intelligent caching
• Build fine-tuning pipelines using LoRA, QLoRA, and full-parameter tuning strategies
• Implement evaluation frameworks that measure factual accuracy, safety, and alignment
• Develop monitoring systems for cost tracking, token usage, and model drift
• Architect RAG systems that ground model outputs in verified knowledge bases

Basic Qualifications

• 4+ years in machine learning engineering with 2+ years focused on LLMs
• Deep understanding of transformer architectures, attention mechanisms, and scaling laws
• Proficiency with PyTorch and the Hugging Face ecosystem
• Experience deploying models on cloud infrastructure (AWS SageMaker, GCP Vertex AI)
• Production experience with vector databases and embedding pipelines

Preferred Qualifications

• Published research or contributions to NLP/ML conferences
• Experience with model quantization, distillation, and on-device deployment
• Background in information retrieval or knowledge graph construction
• Experience with RLHF or preference optimisation techniques

Technologies

Compensation & Benefits

• Competitive salary commensurate with experience and location
• Remote-first work environment with flexible scheduling
• Annual professional development budget for conferences, courses, and tools
• Health, dental, and vision insurance coverage
• Equity participation in the firm's growth
• Equipment stipend for your home office setup