ML Research Engineer — Inference & GPU Kernels

Domain: Machine Learning / AI Experience: 6–10 years Education: PhD/Doctorate, or Master's with a strong research record

Candidates who meet the requirements and provide the requested materials will be prioritized for review. As part of this process, we conduct thorough background checks. Please apply only if you meet these requirements — candidates who meet fewer than 70% of the stated qualifications may be flagged for misrepresenting their professional experience, which could affect eligibility for future project staffing.

Responsibilities

• Design realistic technical scenarios and problem sets within your track
• Author expert-level reference solutions and grading rubrics
• Evaluate AI-generated outputs for correctness, depth, and domain judgment

Required qualifications

• Currently or recently active in the field — hands-on, not purely academic-adjacent
• Strong written communication — you'll be authoring technical explanations and structured feedback, not just doing the work itself
• Comfortable with independent, asynchronous, remote work
• Meets the experience and education bar described in Full Description

Preferred qualifications

• Prior research publication record, open-source contributions, or recognized work product in your track's domain
• Experience evaluating, reviewing, or grading others' technical work (peer review, code review, grading, editing)
• Track-specific bonus signal ML: SGLang, vLLM, Mamba/Mamba2, TensorRT-LLM, or GPU kernel work

Why apply

• Work directly on frontier AI research problems in your area of deep expertise
• Fully remote, flexible, asynchronous — fits around existing work
• Competitive hourly compensation ($100–$170/hr, based on experience)