Staff ML Engineer: Low-Level Kernels & RL Environments

Preference Model; Seattle (WA); On-site; USD 200,000 - 350,000; Full time

Benefits offered by this job

Competitive cash and equity compensation (>90th percentile)

Health, vision, dental benefits

401K match

Lunch provided everyday onsite

Visa sponsorship & relocation support available

Job summary

Preference Model is looking for an experienced Machine Learning Engineer to join the Low Level / Kernels Capabilities team in Seattle, Washington. This role involves developing and optimizing low-level reinforcement learning environments, targeting specific models and difficulty distributions.

The ideal candidate must possess strong skills in C / C++ / CUDA and Python, alongside a deep understanding of hardware. The position offers competitive compensation, ownership in a dynamic startup environment, and the chance to collaborate with leading machine learning engineers.

Qualifications

• Fluent in C / C++ / CUDA, comfortable with assembly.
• Strong Python for production code and automation.
• Write with silicon in mind: memory hierarchy and parallelism.
• Experience writing and optimizing kernels against profilers.
• Ability to create robust, ungameable scoring metrics.
• Experience with large language models.

Responsibilities

• Design and build kernel-focused reinforcement learning environments.
• Implement correctness and performance scoring that cannot be gamed.

Skills

C / C++ / CUDA expertise

Engineering-quality Python

Hardware-aware coding

Kernel development experience

Adversarial mindset

Hands-on work with LLMs

Job description

Preference Model is looking for an experienced Machine Learning Engineer to join the Low Level / Kernels Capabilities team in Seattle, Washington. This role involves developing and optimizing low-level reinforcement learning environments, targeting specific models and difficulty distributions.

The ideal candidate must possess strong skills in C / C++ / CUDA and Python, alongside a deep understanding of hardware. The position offers competitive compensation, ownership in a dynamic startup environment, and the chance to collaborate with leading machine learning engineers.