5 days ago
Montréal, CanadaSenior
Responsibilities
- Build conversational AI systems that understand customer needs and take appropriate actions.
- Develop agent tooling, including memory systems, knowledge graphs, and customization frameworks.
- Train, evaluate, and deploy models for prediction, classification, ranking, and capacity forecasting using Ray Serve and Dagster.
- Create offline and online evaluations, simulations, and CI checks to detect regressions and measure production quality.
- Build shared ML and LLM infrastructure for serving, evaluation, and observability.
- Contribute to design and code reviews, technical writing, and mentorship.
- Monitor and maintain models and agents in production.
Requirements
- At least 6 years of software or machine learning engineering experience, including a track record of shipping ML or LLM systems to production.
- Strong Python skills and software engineering fundamentals.
- Hands-on experience training and deploying ML models, or building with LLMs using prompting, tools, agents, or retrieval.
- Experience with evaluation frameworks, production monitoring, model serving, or related ML platform tooling.
- Familiarity with Ray Serve, Dagster, LiveKit, Vertex AI, GCP, Kubernetes, Pulumi, or AI provider APIs.
- Experience with real-time or streaming systems such as voice, telephony, SIP, WebRTC, or low-latency inference is valuable.
- Comfort working autonomously, navigating ambiguity, and collaborating in a startup or high-growth environment.
Benefits
- Salary range of CAD $200,000 to $250,000 annually.
- On-site work in Montreal, Quebec, Canada.
- Equity and visa sponsorship details were not provided.