Lead AI Engineer

Lead AI Engineer drives the development of intelligent systems that extract & structure data from unstructured documents such as PDFs, scanned forms, and free-text content.

• Lead the architecture, development, and deployment of AI/ML systems for document ingestion, understanding, and data extraction.
• Build and create good datasets and a system of good validation and verification of data and ML systems.
• Build and fine‑tune LLMs and generative AI models to interpret, summarize, and extract information from complex unstructured content.
• Develop NLP pipelines leveraging techniques such as OCR, entity recognition, text classification, summarization, and semantic parsing.
• Integrate LLMs with retrieval systems (RAG), vector databases, and structured outputs suitable for downstream consumption.
• Collaborate cross‑functionally to align technical solutions with product requirements and compliance needs.
• Mentor a team of AI/ML engineers, establish best practices in model training, evaluation, and monitoring.
• Stay abreast of the latest advancements in generative AI and apply cutting‑edge techniques to real‑world document challenges.

• Minimum of seven (7) years of experience in AI/ML engineering, with at least three (3) years in a technical or team leadership role.
• Previous technical leadership in the AI/ML leadership space.
• Hands‑on experience building and deploying S/LLMs or generative AI applications (e.g., using Llama, Deepseek or similar frameworks).
• Proven track record of extracting structured data from unstructured document sources, including scanned forms, free‑text reports, and complex layouts.
• Strong software engineering skills in Python and ML frameworks (e.g., Kubeflow, PyTorch, multi‑agentic frameworks).
• Experience with OCR technologies (e.g., Tesseract, Amazon Textract), NLP techniques, and model deployment in production environments.
• Deep understanding of NLP methods including embeddings, transformers, named entity recognition (NER), and text classification.
• Familiarity with MLOps, version control, CI/CD, and cloud platforms (AWS, GCP, or Azure).

• Experience implementing retrieval‑augmented generation (RAG), prompt engineering, or fine‑tuning foundation models.
• Familiarity with vector databases (e.g., Postgres‑pg‑vector, Pinecone, FAISS, Weaviate) and semantic search.
• Strong experience shipping production ML systems with a track record of monitoring and improving the ML systems.
• Experience working in regulated domains such as healthcare, legal, or finance.

US base salary range for this full‑time position: $ – $. The compensation reflects base salary only.

Lir is an Equal Opportunity Employer that strives to create an inclusive environment, empower employees, and embrace collaborative success.