The role, as published
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.
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
- Health, dental and vision coverage
- 401(k) retirement plan
- Health savings account
Location and work model
- Remote (Canada or UK)
- Full-time
Compensation, as the posting describes it
- Base salary: $250K to $300K
- Equity
- Annual performance bonus
- Flexible time off