Senior Machine Learning Developer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Machine Learning Engineer based in Canada. This is an opportunity to build and ship production-grade ML and AI systems that interact with thousands of customers every day. You’ll develop conversational AI for voice and SMS, enabling agents to understand customer needs, take action, and operate autonomously when appropriate. The role spans product development, machine learning, LLM applications, evaluation systems, and ML infrastructure. You’ll help establish an evaluation-first engineering culture where AI quality is measured continuously before and after release. Working across product squads, you’ll build shared tooling, observability, and platform capabilities that accelerate reliable AI development. You’ll also influence technical standards through design reviews, mentorship, technical writing, and hands-on engineering leadership. This is a highly autonomous role suited to someone who enjoys solving complex problems in a fast-moving, high-growth environment.

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.

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