Senior Machine Learning Engineer
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Posted on the company's own website.
Can I apply?
- Full-time
- Remote from Canada, GB
- Work permit not stated
- $250k–$300k/yr
Senior ML engineering role owning trained models through to reliable, high-volume production serving (latency/throughput tuning, GPU optimization, distributed serving).
Can I apply: the posting is remote and open to candidates in Canada or the UK ("Remote (Canada or UK)"); it is full-time.
Requires senior-level experience, shipped server-side or ML software, inference optimization frameworks, and systems/GPU programming (C++, CUDA, Rust or optimized Python).
Right-to-work status is not stated; salary is listed as $250K to $300K base, currency not specified.
From the posting
- workplace
ATS workplace type: remote
- locations
ATS location: Remote - Canada
- employment types
Full-time
- remote eligible countries
Remote (Canada or UK)
- salary
Base salary: $250K to $300K
- seniority
Senior-level experience, comparable to a senior software or inference engineer at a large technology company.
- job function
Own the path that takes trained machine learning models into reliable production serving
- role family
Hands-on experience with machine learning inference optimization frameworks.
- skills
Proficiency in systems programming and GPU optimization in languages such as C++, CUDA, Rust or optimized Python.
- actionable
Own the path that takes trained machine learning models into reliable production serving
- scam risk
Remote (Canada or UK)
Job description
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
Seen on
- workable — apply.workable.com