Software Engineer (ML Data Infrastructure

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 Stack:

• 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 Big Query, Google Spanner, Google Pub/Sub
• Docker & Terraform

• 4 weeks of vacation to recharge and explore
• Comprehensive health, vision, and dental coverage starting on day one
• RRSP/401(k) with employer match up to 4% to invest in your future from the moment you join
• Top‑of‑the‑line tools and tech to fuel your creativity and productivity
• Toronto HQ perks:
  Steps from Union Station and the PATH, with daily in‑office lunches and dinners

Demonstrated ability to drive projects from 0 to 1, including scoping, execution, and iteration2-5 years developing and shipping large-scale distributed systems with proven ability to manage complexity through thoughtful abstractions and scalable design

Hands-on experience with large-scale data processing systems

Strong fundamentals in data structures, algorithms, and distributed systems

Strong understanding of databases and data storage architectures

Asks great questions, thinks from first principles, and seeks out resources to deepen understanding

Thrives in fast-moving, ambiguous environments with a strong bias toward action

Deep sense of ownership - proactively identifies opportunities, suggests improvements, and acts on them