Sr. AI Engineer (AI/ML Inference)

Dialpad
Vancouver
Workplace: OnsiteFull timeCAD 184,500 - 213,750 annuallyFunction: Data Science & Machine LearningSkills: ["Technical leadership","Mentorship","Pragmatic decision-making","Cross-functional collaboration","Ownership mindset"]

Own production speech and inference systems that power Dialpad’s AI voice agents. You’ll build APIs, services, and deployment workflows to productionize speech models and third-party capabilities, including self-hosted inference and scalable serving. Partner with MLOps (Inference) to ensure reliability through observability, SLOs, incident response, and rollout-safe release infrastructure (shadow traffic, versioning, rollback, and evaluations). Mentor engineers and shape real-time speech operations at scale.

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FursaFursa
Dialpad
Dialpad
3 days ago

Sr. AI Engineer (AI/ML Inference)

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Source: Company careers pageValidated by: Fursa AI
Last checked: 4 hours agoStatus: Live

Job Summary

Own production speech and inference systems that power Dialpad’s AI voice agents. You’ll build APIs, services, and deployment workflows to productionize speech models and third-party capabilities, including self-hosted inference and scalable serving. Partner with MLOps (Inference) to ensure reliability through observability, SLOs, incident response, and rollout-safe release infrastructure (shadow traffic, versioning, rollback, and evaluations). Mentor engineers and shape real-time speech operations at scale.
Location: Vancouver
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Own the end-to-end path from speech model or third-party capability to production, building APIs, services, deployment workflows, and integration layers.
  • •Productionize and operate self-hosted speech models, optimizing serving architecture, resource utilization, concurrency, autoscaling, and cost for real-time voice agents.
  • •Integrate and maintain third-party speech APIs with durable abstractions, including failover, capacity planning, version management, and provider monitoring.
  • •Implement reliability engineering for customer-facing speech systems via monitoring, alerting, dashboards, health checks, and incident-response practices to meet uptime/latency/quality SLAs.
  • •Enable safe releases and evaluation infrastructure (shadow traffic, staged rollouts, versioning, rollback-safe releases, and model comparisons) while mentoring engineers.

Pay and Benefits

Salary: CAD 184,500 - 213,750 annually

Key Requirements

  • •Strong software engineering fundamentals and experience designing maintainable APIs, services, and integration layers, with Python proficiency.
  • •5+ years building or operating production software, including ML-backed systems or other latency-sensitive, real-time services.
  • •Hands-on experience deploying, scaling, and troubleshooting ML models in production, including model serving and inference optimization.
  • •Experience with cloud infrastructure and distributed systems, including familiarity with containers, orchestration, service networking, CI/CD, and GCP.
  • •Demonstrated cross-functional technical leadership with ML scientists, MLOps/inference engineers, and product teams, including mentoring and trade-off decisions across quality, reliability, latency, scale, and cost.
Experience:ML-backed systemsReal-time servicesSpeech applicationsStreaming mediaLatency-sensitive systems
Skills:Technical leadershipMentorshipPragmatic decision-makingCross-functional collaborationOwnership mindset
Languages:English
Tech Stack:PythonGCPContainersOrchestrationService networkingCI/CDDistributed systemsML model servingInference optimization

Company Brief

Dialpad
Provides cloud-based business communications platform offering voice, video, messaging, contact center, and AI-driven call intelligence to help teams communicate and collaborate across devices and locations.
Industry: SaaS
Company Size: Enterprise (1,001+ employees)
Growth: Scaleup
Headquarters: San Francisco, United States
Founded: 2011
WebsiteLinkedIn