Senior Machine Learning Developer

Accountabilities:

• • Build conversational AI systems for phone and SMS that understand customer needs, perform actions, and determine when autonomous behavior is appropriate.
  • Develop AI tooling such as memory systems, knowledge graphs, and validated customization capabilities that enable agents to adapt to different business needs.
  • Train, evaluate, deploy, and maintain ML models for prediction, classification, ranking, and capacity forecasting using technologies such as Ray Serve and Dagster.
  • Create offline and online evaluations, simulations, and CI quality gates to identify regressions and continuously measure AI performance.
  • Develop shared evaluation, observability, and LLM tooling that enables product teams to deliver AI capabilities more quickly and reliably.
  • Contribute to ML platform capabilities including model serving, LLM infrastructure, and production monitoring.
  • Drive engineering quality through design and code reviews, technical documentation, and mentorship.
  • Take ownership of projects from problem definition through deployment, monitoring, iteration, and continuous improvement.
  • Help turn lessons learned from individual product teams into reusable platform capabilities.

  Requirements:

  • 6+ years of experience in software engineering or machine learning engineering, with demonstrated experience shipping ML- or LLM-powered systems to production.
  • Strong Python skills and solid software engineering fundamentals, with an emphasis on maintainable, testable, and reliable code.
  • Hands-on experience developing AI systems, including ML model training and deployment and/or LLM applications involving prompting, tool use, agents, retrieval, or related technologies.
  • Strong understanding of how AI systems behave in production and the ability to identify limitations, failure modes, and quality issues.
  • An evaluation-first mindset, with the ability to use measurement and experimentation to distinguish genuine improvements from noise or regressions.
  • Comfort working independently in ambiguous product environments, with sound judgment around when to prioritize depth, speed, or experimentation.
  • Strong ownership and communication skills, with the ability to take initiatives from problem framing through production delivery and ongoing improvement.
  • Experience with ML platforms, evaluation frameworks, model serving, feature or prompt registries, or ML observability is a plus.
  • Familiarity with technologies such as LiveKit, Ray Serve, Dagster, Vertex AI, GCP, Kubernetes, Pulumi, or AI provider APIs is beneficial.
  • Experience taking models or AI agents from prototype to production and owning their ongoing performance is advantageous.
  • Familiarity with real-time or streaming technologies, including voice, telephony, SIP, WebRTC, or low-latency inference, is a plus.
  • Startup or high-growth technology experience is beneficial.

  Benefits:

  • Base salary range of $200,000–$250,000 CAD.
  • Equity package.
  • Flexible paid time off.
  • Fully covered group insurance.
  • Opportunities for professional growth and career advancement.
  • Opportunity to work on AI technology with real-world customer interactions at significant scale.
  • Exposure to a broad range of machine learning, conversational AI, LLM, and production infrastructure challenges.