Senior Machine Learning Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 5d ago
The date the source published, not the day we noticed it (2026-10-29). Last seen at its source just now.
We have tracked this listing since 29 Oct 2026 (4 days). The employer's own board has carried it every time we have read it, most recently just now.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
Canada
The description agrees: it names Canada, United Kingdom.
What the ad says
…Remote (…) Canada or UK…
Pay
$250k–300k/yr
Read out of the job description by us, not from a structured field. Shown in the posting's own currency and period; we never convert.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Workable employer's own board first seen 4d ago · last seen just now
The listing
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