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Snowflake is seeking a Software Engineer to join the Cortex AI Functions Platform team. This team builds the infrastructure that enables Snowflake customers to call AI directly from SQL, running models over their own data without moving it out of the platform. The platform must handle inference requests at data warehouse scale—where a single SQL statement can expand into large volumes of requests that must complete predictably, within expected cost, and without compromising query performance when dependencies degrade or fail.
Current projects include architecting multi-modal inference capabilities, implementing quality gates for shipping new functions and models at batch scale, and extending support for input data beyond plain text. The team continuously optimizes for throughput, cost, and reliability as customer usage grows, and improves failure detection, diagnosis, and recovery in the inference path.
In this role, you will think creatively to solve complex, often ambiguous problems; participate in all stages of platform development from design through production support; work closely with research teams, product, and engineering partners to shape product strategy; and mentor less experienced engineers.
Note: A research background, including pre-training or fine-tuning models, is not required for this role.
REQUIREMENTS:
- 4+ years of experience building production backend or distributed systems in C++, Java, Go, Python, or comparable language
- BSc in a technical field (CS, EE, Physics, Math, etc); MSc/PhD is a plus
- Experience designing and operating high-throughput services, including handling concurrency, backpressure, partial failures, and observability
- Experience designing service or RPC APIs (REST, gRPC)
- Software engineering best practices (programming, testing, version control, CI/CD, containers, agile development)
- Experience building distributed systems that guarantee high throughput without compromising reliability
- High curiosity and enthusiasm for open-ended problems; ability to turn loosely defined problems into scoped, testable designs
- Ability to articulate results and complex concepts to leadership
- Ability to produce solutions independently and work effectively in teams
- Experience with SQL engines, query execution, or large-scale data systems is a strong asset
- Hands-on MLOps experience (e.g., deploying ML models) is a plus
