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Raydar

Senior Machine Learning Engineer

Posted 3 Days Ago
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Remote
Hiring Remotely in Canada
Senior level
Remote
Hiring Remotely in Canada
Senior level
Own the production deployment and optimization of machine learning models at high request volumes. Responsibilities include reducing inference latency, improving throughput, profiling GPU code, containerizing models, designing distributed multi-GPU serving systems, and applying quantization, batching, caching, compression, and knowledge-transfer techniques. The role requires strong systems programming, GPU optimization, distributed systems, container orchestration, and production software experience.
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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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