AI / ML Engineer - AI Trainer
About the Company
AfterQuery is a research lab exploring the capabilities and limits of artificial intelligence through specialized datasets and experimentation. The company focuses on high-quality, human-generated data and supports leading AI labs. It is backed by investors including Y Combinator and Box Group.
About the Role
AfterQuery is building a research cohort of experienced machine learning professionals specializing in inference systems, GPU kernel engineering, and large-model deployment infrastructure. This role focuses on research and evaluation rather than production engineering. You will use your technical expertise to develop realistic problems, create reference solutions, and evaluate AI-generated outputs against expert-level standards. The position is fully remote, flexible, and asynchronous, making it suitable for professionals who want to contribute alongside existing commitments. The role typically requires 6–10 years of experience and a PhD or doctorate, or a master's degree supported by a strong research record.
Key Responsibilities
Design realistic technical scenarios and problem sets within your area of expertise. Develop expert-level reference solutions and detailed grading rubrics. Evaluate AI-generated outputs for correctness, technical depth, and sound domain judgment. Write clear technical explanations and structured feedback to assess AI performance on complex problems. Apply practical knowledge of ML inference, GPU kernel optimization, and large-model deployment to research and evaluation tasks. Required Qualifications 6–10 years of relevant professional experience. A PhD or doctorate, or a master's degree with a strong research record. Current or recent hands-on experience in the relevant technical field. Strong written communication skills, including the ability to author technical explanations and structured feedback. Ability to work independently in a remote, asynchronous environment. Deep expertise in machine learning inference, GPU kernels, inference serving systems, or large-model deployment infrastructure.
Preferred Qualifications
Research publications, open-source contributions, or recognized work in the relevant technical domain. Experience evaluating or reviewing technical work through peer review, code review, grading, or editing. Familiarity with ML inference and optimization technologies such as SGLang, vLLM, Mamba/Mamba2, TensorRT-LLM, or GPU kernel engineering. Salary & Benefits Hourly compensation: $100–$170, depending on experience. The listing header displays $135 per hour. Fully remote work with flexible, asynchronous scheduling. Opportunities to contribute to frontier AI research and evaluation. Flexibility to work around existing professional commitments. Work Location This is a fully remote contract position listed in New York, NY. The work is designed to be flexible and asynchronous. Application Requirements Applicants should submit a resume. Candidates who meet the experience and education requirements and provide the requested materials will be prioritized for review. The hiring process includes thorough background checks.