1 day ago
Toronto, CanadaStaff+
Responsibilities
- Define and lead technical architecture for enterprise-scale AI and ML platforms.
- Design scalable, resilient, reusable AI systems for mission-critical workloads.
- Establish architectural standards, engineering patterns, and deployment and operations best practices.
- Transform AI research prototypes into production-grade solutions involving LLMs, trustworthy AI, and agentic AI systems.
- Lead model serving, inference optimization, agent architecture, orchestration, observability, and AI infrastructure decisions.
- Drive MLOps, LLMOps, and AI platform engineering practices while improving scalability, maintainability, and operational readiness.
- Own operational excellence, reliability, performance, and availability of AI products.
- Lead responses to complex production incidents, model failures, performance degradation, and system outages.
- Establish monitoring, alerting, incident management, capacity planning, and SLO practices for AI systems.
- Mentor AI and ML engineers, conduct architecture reviews, provide design guidance, and promote technical and operational ownership.
Requirements
- 10+ years of experience in software engineering, machine learning engineering, AI engineering, or related technical disciplines.
- Deep expertise designing, deploying, and supporting large-scale AI and ML systems in production.
- Demonstrated success leading complex technical initiatives from concept through deployment and ongoing operations.
- Strong knowledge of software architecture, reliability engineering, observability, MLOps, DevOps, and cloud technologies.
- Proven ability to mentor engineers and lead teams through complex technical and operational challenges.
- Preferred: experience with foundation models, LLMs, agentic AI architectures, and multi-agent workflows.
- Preferred: experience with trustworthy or responsible AI, AI governance, model risk management, inference optimization, AI infrastructure, regulated environments, or mission-critical production systems.
Benefits
- Hybrid working model designed to combine flexibility with in-person learning, collaboration, and connection.
- Opportunity to work with AI researchers and develop advanced AI systems at enterprise scale.
- Opportunity to bridge cutting-edge research with client value and meaningful business outcomes.
Categories
AI ResearchML Engineering
About Vanguard
Vanguard is an investment management company offering low-cost index and active mutual funds, ETFs, brokerage, retirement plans, and financial advice for individual, institutional, and advisor clients. Founded in 1975 by John C. Bogle and headquartered in Valley Forge, PA, it operates a client-owned structure in which its funds own the firm. Its business model centers on asset-based management and advisory fees.