Design LLM applications using Python, RAG, embeddings, and vector search for National Safety Services Inc. in Canada. Translate safety requirements into practical AI solutions.
This Machine Learning Engineer will develop intelligent applications supporting NSS’s occupational health and safety technology direction. You will work with OpenAI, Gemini, or similar LLM APIs, alongside LangChain or LangGraph frameworks. Your contributions will span document processing pipelines, compliance assessments, risk identification, and gap analysis while supporting production reliability.
Key Responsibilities:
- Design and deploy LLM-powered applications from prototype through MVP
- Implement RAG, embeddings, vector search, and document processing pipelines
- Translate regulatory requirements into practical AI-powered solutions
- Collaborate with occupational health and safety subject matter experts
- Troubleshoot challenges and communicate technical decisions to senior leadership
Requirements:
- Five or more years in machine learning engineering, applied AI, or related roles
- Robust Python skills and experience with ML frameworks and development tools
- Experience using LLM APIs such as OpenAI or Gemini
- Ability to explain architecture, trade-offs, resources, and risks clearly
- Critical, independent thinking with intellectual curiosity and willingness to learn
Bring LLM engineering, document analysis, and Python expertise to NSS’s AI modernization of occupational health and safety systems.