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.