AI/ML Engineer (Montreal)

Key Responsibilities:

• Design & Deploy Conversational / Multi-Agent LLM Solutions
• Craft multi-agent conversational flows capable of handling a wide range of user requests—both purely informational and action-oriented.
• Employ advanced LLM techniques (prompt engineering, context retrieval, multi-step reasoning) to ensure robust, context-aware dialogues


• Multi-Modal & Multi-Model Integration
• Explore different input/output formats (e.g., text, potential voice or image-based flows) to enrich user interactions
• Evaluate different models based on their intended use case, considering both technical capabilities and cost efficiency


• Platform & Pipeline Building
• Work with cross-functional teams to design data pipelines that feed your models real-time or near real-time data
• Implement best practices around model lifecycle management—versioning, containerization, deployment orchestration, etc


• Optimization & Scale
• Ensure the chat system can handle thousands (eventually millions) of concurrent interactions, maintaining low latency and high availability
• Monitor performance, define metrics (latency, user success rate, fallback rate, etc.), and iteratively improve


• Ongoing Innovation & Experimentation
• Remain current on the rapidly evolving AI/ML landscape, especially in generative models, multi-agent orchestration, and knowledge retrieval
• Propose new ways to extend AI across our platform—e.g., advanced personalization, proactive customer engagements, etc.

Qualifications:

• Core AI/ML Expertise
• 3+ years hands-on experience building and deploying machine learning solutions at scale
• Solid understanding of NLP techniques, including transformer models and embeddings, with hands-on experience using modern tools like Hugging Face, AWS Bedrock, and OpenAI’s API


• Backend & Data Infrastructure
• Proficient in Python or a similar language for data pipelines and model development
• Experience with cloud platforms (AWS strongly preferred), containerization (Docker, Kubernetes), and microservices


• Research & Problem-Solving Mindset
• Up-to-date on AI/ML trends—especially in multi-agent systems, generative modeling, or multi-modal approaches
• Skilled at diagnosing bottlenecks, scaling solutions, and balancing innovation against real-world constraints


• Collaboration & Communication
• Comfortable presenting complex ML concepts to non-technical stakeholders
• Passion for iterative development—able to pivot based on user feedback and product metrics.

Bonus Points:

• Familiarity with vector search solutions (e.g. Pinecone, Weaviate, or Elasticsearch with vector plugins)
• Familiarity with building or deploying large language models and related tooling in the AWS Bedrock ecosystem
• Experience designing or contributing to multi-agent LLM frameworks or orchestrations (e.g., specialized agent-based approaches in advanced NLP)

Benefits:

• Competitive salary 150k CAD - 240k CAD (based on experience)
• Flexible working hours
• Supplemental health insurance
• Professional development stipend
• $500 wfh tech set-up reimbursement