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Delos Data Inc

Software Development Engineer in Test - AI

Montréal, Quebec, Canada

Location
Montréal, Quebec, Canada
Work
Hybrid
Employment
Full-time
Level
Not stated
Function
Engineering
Pay
CA$120K – CA$180K a year (read from the ad)
Posted
3 weeks ago

About the role

Software Development Engineer in Test - AI

About us

We are a startup building foundational technology to address performance, scalability, and resiliency challenges in large-scale AI data center clusters. We are backed by top-tier VC firms and notable angel investors.

The company is led by experienced builders and operators who have founded companies, taken them to scale, and exited successfully. We work with a strong sense of unity and shared responsibility, and we expect trust, integrity, and respect in how we collaborate and make decisions. We hold ourselves accountable to one another and to the quality of the work we deliver.

Headquartered in Silicon Valley, we operate across a mix of remote and on-site locations in the U.S. and Canada. We aim to create an environment where people are treated fairly, supported in their growth, and are empowered to do meaningful work alongside others who take the craft seriously.

Some Recent Press: https://www.eetimes.com/startup-boosts-scale-up-to-1000-gpus-in-a-single-domain/

We are looking for

We are looking for a Software Development Engineer in Test (SDET) to ensure the reliability and performance of our core AI infrastructure. In this role, you are an engineer who builds sophisticated automation frameworks and stress-testing suites to break and then harden our system.

You will be responsible for validating the intersection of distributed systems, GPU kernels, and AI frameworks. You will build a scalable foundation of trust in our code, ensuring that our performance-critical primitives work every time, at any scale.

Key Responsibilities

  • Design, develop, and maintain a robust automated testing framework from the ground up that supports distributed AI training and inference workloads.
  • Develop complex test plans that go beyond unit tests, focusing on end-to-end system integration, stress testing, and hardware-software boundary conditions.
  • Partner closely with System Engineers to debug deep-seated issues in distributed clusters, using telemetry and profiling tools to identify bottlenecks.

Required Skills and Qualifications

  • Strong proficiency in Python (for automation and orchestration).
  • Proven experience building or extending test automation frameworks for complex back-end systems.
  • Proven ability to troubleshoot automated test failures within complex large-scale distributed systems, and identify root causes.
  • Experience with containerization (Docker/Kubernetes) and modern CI/CD tools (GitHub Actions, GitLab CI, or Jenkins).

Desired Skills

  • Experience with Kubernetes or Terraform or Ansible for managing test-bed environments.
  • Experience testing high-performance networking protocols or distributed file systems.
  • Experience testing software that interacts directly with drivers or firmware.

Education

  • Bachelor's or Master's degree in Computer Engineering, Computer Science, or a related field.

Location

This is a hybrid role based in Montreal.

Compensation

Target base salary for this role is $120,000 - $180,000 CAD per year + meaningful equity + benefits + RRSP. Our salary ranges are determined by role, level, experience, and location.

We are an equal opportunity employer. We value a range of perspectives and experiences and make employment decisions based on merit and business needs. We do not discriminate on the basis of legally protected characteristics.

Agency Note

We do not accept resumes from agencies or search firms. Please do not forward candidate profiles through our careers page, email, LinkedIn messages, or directly to company employees. Any resumes submitted will be deemed the property of the company, and no fees will be paid in the event the candidate is hired.

#LI-EW1

Source

Posted by Delos Data Inc on their own hiring page, jobs.ashbyhq.com. OptiTalent shows it as published, read 07 Nov 2026 03:00 UTC; the original is the reference.

View the original ad ↗

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