Data Scientist 3 / Scientifique de données 3- 19457

emergiTEL Inc.; Canada; Remote; CAD 85,000 - 115,000; Full time

Job summary

A technology solutions provider in Canada is seeking a Data Scientist LLM Specialist to develop cutting-edge AI solutions. The role involves designing and deploying conversational agents, optimizing large language models, and ensuring robust integration in the cloud. Candidates should have substantial experience in NLP and AI development, alongside strong programming skills. This position offers a collaborative environment within a dedicated data science team.

Qualifications

• 5+ years of experience in ML/AI development.
• Strong expertise in NLP and LLMs.
• Experience fine-tuning and deploying large language models.

Responsibilities

• Develop AI-powered conversational agents leveraging LLMs.
• Design prompt engineering strategies to optimize model outputs.
• Deploy and monitor production-ready AI solutions on GCP.

Skills

NLP expertise

LLM development

prompt engineering

knowledge retrieval

cloud deployment

Education

Bachelor’s, Master’s, or PhD in Computer Science or related field

Tools

Python

ML/DL frameworks (PyTorch, TensorFlow, Hugging Face)

Git, GitHub

Job description

Overview

DATA SCIENTIST - LLM SPECIALIST: Chatbot & AI Assistant Development

As a LLM Specialist and Data Scientist, you'll join our innovative team developing next-generation conversational AI solutions. You will be instrumental in designing, developing, and deploying sophisticated chatbots and AI assistants that transform how our business interacts with customers. Working alongside talented engineers and product teams, you'll leverage cutting-edge Large Language Models to create intelligent, context-aware conversational experiences while ensuring robust deployment in our Google Cloud infrastructure.

Core Responsibilities – AI/LLM Engineer

• Develop AI-powered conversational agents leveraging state-of-the-art LLMs such as GPT-4, Claude 3.5, and Gemini 2.0.
• Design and implement prompt engineering strategies to optimize model performance and outputs.
• Build and enhance RAG (Retrieval Augmented Generation) pipelines for efficient knowledge retrieval and response generation.
• Deploy, maintain, and monitor production-ready AI solutions on Google Cloud Platform (GCP).
• Drive continuous improvement, monitoring, and deployment of AI systems to ensure reliability, scalability, and performance.

Qualifications

• Strong expertise in NLP, LLMs, and conversational AI development, with 5+ years of experience in ML/AI development.
• Proven ability to fine-tune, optimize, and deploy large language models for production-grade, scalable AI solutions.
• Skilled in prompt engineering, chain-of-thought reasoning, vector databases, semantic search, RAG pipelines, transfer learning, model evaluation, and Responsible AI practices.
• Bachelor’s, Master’s, or PhD in Computer Science, AI, or related field, preferably with a focus on NLP/ML & LLMs.

Technical Requirements

1. Advanced NLP & LLM Expertise
2. Hands-on experience with LLM frameworks such as LangChain and LlamaIndex.
3. Knowledge of Model Context Protocols (MCPs), containerization, microservices, and MLOps practices.
4. Experience in LLM deployment optimization, semantic caching, streaming implementations, and multi-cloud LLM providers (OpenAI, Anthropic, Google).
5. Hands-on experience fine-tuning and deploying large language models (e.g., GPT, BERT, T5).
6. Experience with chatbot frameworks (e.g., Rasa, Botpress, Microsoft Bot Framework).
7. Knowledge of context management and multi-turn conversation handling.
8. Deep understanding of prompt engineering and LLM optimization techniques.
9. Experience with LLM evaluation metrics and performance optimization.
10. Experience with function calling and tool use in LLM applications.
11. Familiarity with multi-agent systems and agent coordination.
12. Strong understanding of Gen AI memory management and state persistence.

Data Processing & Engineering

• Proficiency in Python and relevant ML/DL frameworks like PyTorch, TensorFlow, Hugging Face
• Experience with API development and integration (REST APIs, GraphQL)
• Version control and collaboration tools (Git, GitHub)

Miscellaneous Requirements

• Google Cloud Platform (GCP) familiarity and enterprise security & compliance requirements.

Nice to Have Skills

• Experience with chatbot frameworks (e.g., Rasa, Botpress, Microsoft Bot Framework)
• Knowledge of enterprise security and compliance requirements for AI systems
• Understanding of chatbot analytics and performance monitoring
• Experience with hybrid approaches combining rule-based and AI-powered responses

History of the role: New role

Team size and environment: 10 data science & AI team