About this role
AfterQuery is seeking a full-time Research Engineer based in San Francisco to design and run training experiments that isolate the impact of datasets on model behavior. This role suits professionals with at least two years of machine learning experience who want to build high-leverage ML infrastructure and shape the future of artificial intelligence.
Role Overview
As a Research Engineer, the chosen candidate will design and run controlled supervised fine-tuning (SFT) and reinforcement learning (RL) post-training experiments to measure how different data sources, structures, and selection strategies affect capability, generalization, and alignment. The position involves owning the full experiment loop from formulating hypotheses and building pipelines to running models, analyzing results, identifying confounders, and determining the next steps. The work is empirical and fast-paced, partnering with frontier AI labs to turn datasets into clear, defensible evidence of improvement.
Key Responsibilities
Requirements
Skills and Tools
Salary and Benefits
About the Company
AfterQuery is an applied research lab curating data solutions for foundation model development, based in San Francisco. The company serves frontier AI labs with the mission of delivering the best data to power the best models. Backed by leading investors including Altos Ventures, BoxGroup, and Y Combinator, alongside angels from Google DeepMind, OpenAI, Anthropic, Meta Superintelligence Labs, and Microsoft AI, AfterQuery sits directly in the loop of how foundational AI systems improve.
How to Apply
Interested candidates should apply directly on the official AfterQuery careers page.
Skills and tech stack
Questions candidates ask
What is the location of the Research Engineer role?
The position is based in San Francisco, California.
What is the salary range for this position?
The salary ranges from $210,000 to $450,000 USD per year.
How many years of experience are required?
At least 2 years of professional experience in machine learning engineering, research engineering, ML infrastructure, or a closely related field is required, with 2-4+ years preferred.
What technical skills and tools are needed?
Required tools and technologies include Python, PyTorch, JAX, Ray, and Slurm, along with experience in LLM fine-tuning and building production-quality ML infrastructure.
What benefits are provided to eligible employees?
Eligible employees receive health insurance (medical, vision, dental), a 401(k) with employer match, a daily UberEats stipend for meals, a monthly wellness stipend, and meaningful equity.