Posting record
Open 4+ days
- Raydar's site dates the posting
- Ghostless first sees this listing
- Last checked: still up
How we know
It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.
Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Raydar, so its true age is longer.
Last checked Nov 4, 2026.
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Upload your resumeWhat it asks of you
- PhD asked for
What the posting discloses
- Pay
- $250k to $300k a year CAD
Base salary: $250K to $300K (quoted from the posting)
Not stated: Real vacancy, AI screening.
Why these three
Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.
Skills mentioned
About the role
About the company
Our client is a software company.
The role
Raydar is recruiting for this role on behalf of our client. Own the path that takes trained machine learning models into reliable production serving, with a focus on speed, efficiency and dependability at high request volume. The work combines performance tuning of models and GPU-based code with the design of distributed serving systems that run across many machines.
What you'll do
- Optimize serving latency and throughput for machine learning models.
- Take models from research through containerization and into stable production deployment.
- Profile and tune code to make efficient use of GPU hardware.
- Design and run distributed serving systems across multiple GPUs and nodes.
- Apply model acceleration methods such as quantization, batching and caching.
Requirements
What we're looking for
- Senior-level experience, comparable to a senior software or inference engineer at a large technology company.
- Track record of developing server-side or learning-based software and getting it running live for real users.
- Hands-on experience with machine learning inference optimization frameworks.
- Proficiency in systems programming and GPU optimization in languages such as C++, CUDA, Rust or optimized Python.
- Familiarity with methods that speed up and shrink models, such as weight compression, knowledge transfer between models or token prediction.
- Experience with distributed systems, container orchestration and handling high concurrency.
- Based in an eligible country for this remote role.
Bonus points
- Public technical work, such as open-source contributions to inference engines or detailed technical write-ups.
- A history of internal progression and promotions within one employer.
- A doctorate in a quantitative field, or equivalent hands-on systems experience, with study at a leading university as a further advantage.
Benefits
Compensation and benefits
- Base salary: $250K to $300K
- Equity
- Annual performance bonus
- Health, dental and vision coverage
- Flexible time off
- 401(k) retirement plan
- Health savings account
Location and work model
- Remote (Canada or UK)
- Full-time
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