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Salary: CAD 146,000 - 219,000 / annual
Snowflake is seeking a Software Engineer — AI to join its Toronto engineering team, working on the company's AI Data Cloud platform. You will design, develop, and ship AI-powered systems and services used by thousands of organizations worldwide, focusing on production AI infrastructure at scale.
Key responsibilities include:
- Design, develop, and ship AI-powered features and services across model inference, AI functions, retrieval systems, and intelligent application experiences on the Snowflake platform
- Build production-quality infrastructure for AI workloads, including model serving, embedding pipelines, retrieval-augmented generation (RAG), and AI-driven automation
- Write clean, performant, and well-tested code in Python, Java, C++, or Go, contributing to systems operating at enterprise scale across Snowflake's multi-cloud infrastructure
- Collaborate with ML researchers, senior engineers, and product managers to translate AI research and product requirements into robust, scalable engineering solutions
- Participate in system design, design reviews, and propose architectural improvements to shape the technical direction of AI services
- Own work end-to-end from design and implementation through testing, deployment, monitoring, and operational health
- Stay current on AI/ML advancements and evaluate new techniques, models, and tools for applicability to Snowflake's platform
- Contribute to engineering culture through code reviews, documentation, knowledge sharing, and continuous improvement of team practices
Snowflake's AI/ML engineering teams are delivering the intelligence layer powering Cortex AI, large language model inference, AI functions, intelligent search, and next-generation AI-powered experiences. You'll work on problems at the frontier of enterprise AI, with code shipping to production and impacting real customers.
REQUIREMENTS:
Required:
- 3+ years of software engineering experience building production systems, with strong foundation in computer science fundamentals (data structures, algorithms, distributed systems)
- Experience with AI/ML systems: model serving, inference pipelines, LLM integration, embedding systems, or AI-powered application features in production environment
- Proficiency in one or more of: Python, Java, C++, or Go
- Experience building distributed systems or cloud-native services; understanding of scale, reliability, and performance challenges in multi-cloud environments
- Strong problem-solving skills and ability to break down ambiguous problems into clear engineering tasks
- Collaborative mindset; effective work with engineers, researchers, and product managers with clear communication
- Ownership mentality; responsibility for work from design through production with focus on quality, reliability, and operational excellence
Preferred:
- Experience with LLM inference, fine-tuning, RAG architectures, or vector search at production scale
- Familiarity with ML frameworks such as PyTorch, TensorFlow, or similar
- Experience with cloud infrastructure (AWS, Azure, or GCP) and containerization (Docker, Kubernetes)
- Background in data platforms, data warehousing, or SQL-based systems
- Experience with CI/CD pipelines, automated testing, and production monitoring/observability
- Contributions to open-source AI/ML projects or published research in AI/ML
