Software Engineer (ML Data Infrastructure)
Toronto, Ontario, Canada
Mid Level
Full-Time
About the role
- We’re seeking an experienced engineer to join our team as a Software Engineer, ML Data Infrastructure
- You’ll collaborate with exceptional engineers to build cutting-edge AI design experiences that delight millions of users
- Tackling complex technical challenges collaboratively, from scaling distributed systems to enabling new generative media experiences
- Building robust data infrastructure that powers foundation models at petabyte scale, ensuring reliability and performance across multi-modal training pipelines
- Optimizing data processing workflows for massive throughput, working hands-on with distributed systems, TPU infrastructure, and large-scale storage solutions
- Partnering with research scientists to understand data requirements and translating them into production-grade systems that accelerate model development cycles
- Our backend infrastructure is primarily written in Python and makes use of the following technologies (experience with them is helpful but not strictly required):
- Kubernetes
- GCP, Google Bigtable, Google BigQuery, Google Spanner, Google Pub/Sub
- Docker & Terraform- Strong fundamentals in data structures, algorithms, and distributed systems
- Hands-on experience with large-scale data processing systems
- 2-5 years developing and shipping large-scale distributed systems with proven ability to manage complexity through thoughtful abstractions and scalable design
- Strong understanding of databases and data storage architectures
- Demonstrated ability to drive projects from 0 to 1, including scoping, execution, and iteration
- Deep sense of ownership - proactively identifies opportunities, suggests improvements, and acts on them
- Thrives in fast-moving, ambiguous environments with a strong bias toward action
- Asks great questions, thinks from first principles, and seeks out resources to deepen understanding