Senior Machine Learning Engineer

Numa

. Build conversational AI systems for phone and SMS that understand customer needs, take action, and determine when to act autonomously .

Posted 9/23/2026full-timeRemote • CanadaSenior💰 CA$200,000 - CA$250,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying conversational AI systems and machine learning models, with a strong focus on evaluation and improvement metrics. Proficient in Python and experienced in navigating ambiguity within product environments while maintaining high engineering standards.

Highest-signal resume keywords

Machine Learning EngineeringConversational AI DevelopmentPython ProgrammingModel Training and DeploymentEvaluation Frameworks

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningConversational AIPythonModel TrainingModel DeploymentPredictionClassificationRankingEvaluation MetricsSoftware Engineering

Soft Skills

CommunicationOwnershipProblem FramingMentorshipAutonomy

Tools & Technologies

Ray ServeDagsterGCPKubernetesLiveKitVertex AIPulumiOpenAIDeepgramElevenLabs

Industry Keywords

AI SystemsLLMProduction ML ModelsEvaluation FrameworksReal-Time Systems

Tech Stack

Tools & technologies

Google Cloud PlatformKubernetesPythonRay

About the role

Key responsibilities & impact

Build conversational AI systems for phone and SMS that understand customer needs, take action, and determine when to act autonomously
Develop memory, knowledge graphs, and validated customization tooling for dealership-focused agents
Train, evaluate, and deploy ML models using Ray Serve and Dagster for prediction, classification, ranking, and capacity forecasting
Maintain ML models in production
Create offline and online evaluations, simulations, and CI gates to measure quality and catch regressions
Implement shared evaluation, observability, and LLM tooling
Contribute to model serving, LLM infrastructure, and production observability
Raise engineering standards through design and code reviews, technical writing, and mentorship
Work autonomously and help create clarity in ambiguous situations
Ship AI features including prompts, agents, tools, and production ML models that interact with real customers

Requirements

What you’ll need

6+ years of software or machine learning engineering experience
Track record of shipping ML or LLM powered systems to production
Strong Python and solid software engineering fundamentals
Hands-on experience building AI systems
Experience training and deploying ML models for prediction, classification, and ranking and/or working with LLMs, prompting, tool use, agents, and retrieval
Evaluation-first approach and ability to use measurement to assess improvements and regressions
Comfort operating with meaningful ambiguity in a product environment
Ownership and communication skills to carry work from problem framing through shipping, monitoring, and improvement
Nice to have: ML platform and tooling experience, including evaluation frameworks, model serving, feature/prompt registries, or ML observability
Nice to have: Familiarity with LiveKit, Ray Serve, Dagster, Vertex AI, GCP, Kubernetes, Pulumi, Anthropic, OpenAI, Deepgram, or ElevenLabs
Nice to have: Real-time or streaming systems experience, including voice, SIP/WebRTC, or low-latency inference
Nice to have: Startup or high-growth environment experience

Benefits

Comp & perks

Equity Packages
Flexible PTO
Fully Covered Group Insurance
Opportunities for career advancement
Everyone's growth
Category-defining AI technology and industry leadership exposure