Remote Low-Level Engineer: Kernel & Inference Optimization

Open Data Science; San Francisco (CA); Remote; USD 123,984 - 172,200; Full time

Job summary

A cutting-edge AI company is looking for Low-Level Engineers to design RL environments that optimize kernel development and systems programming. Candidates should have strong Python skills and a solid understanding of LLMs. This remote contractor role offers an hourly rate ranging from $90 to $125, based on expertise. Applicants will contribute to the creation of feedback loops for model training across various architectures. A minimum of 4 hours overlap with PST and proficiency in advanced English is mandatory.

Qualifications

• Strong Python programming skills are essential.
• Clear understanding of LLMs and their limitations is required.
• Experience with memory hierarchies and performance implications.
• Knowledge of threading models and concurrent programming.
• Familiarity with compiler frameworks and GPU architectures.

Responsibilities

• Design and build MLE/SWE environments for language models.
• Target specific language models and ensure difficulty distribution.

Skills

Strong Python

Clear understanding of LLMs

Memory hierarchies knowledge

Threading models understanding

Cache coherence knowledge

AOT compilation expertise

Modern C++ proficiency

Assembly-level programming

Debugging GPU kernels

Custom PyTorch operators

GPU communication libraries knowledge

Mixed-precision kernels understanding

Job description

A cutting-edge AI company is looking for Low-Level Engineers to design RL environments that optimize kernel development and systems programming. Candidates should have strong Python skills and a solid understanding of LLMs. This remote contractor role offers an hourly rate ranging from $90 to $125, based on expertise. Applicants will contribute to the creation of feedback loops for model training across various architectures. A minimum of 4 hours overlap with PST and proficiency in advanced English is mandatory.