Machine Learning Researcher

HHM Talent•San Francisco, CA

1d•$150,000 - $300,000•Onsite

About The Position

The Machine Learning Researcher will own cutting-edge research in mechanistic interpretability, context compression, and transformer training. Researchers drive projects end-to-end-from developing hypotheses and curating datasets to training models on large GPU clusters, evaluating results, and deploying models into production. This is a highly autonomous research role where shipping impactful models matters more than publishing papers.

Requirements

Experience training machine learning models from scratch with full ownership of data, architecture, and training.
Strong understanding of transformers and modern deep learning techniques.
Hands-on experience with large-scale model training and experimentation.
Research mindset focused on rapid experimentation and production impact.
High agency and ability to self-direct research.
Willingness to work onsite in San Francisco in a fast-paced startup environment.

Nice To Haves

Experience pretraining transformer models.
Reinforcement learning or post-training experience for LLMs.
Novel architecture or training method development with measurable results.
Experience at frontier AI labs, leading university research groups, or early-stage AI startups.
Exceptional technical achievements such as Kaggle, ICPC, IOI, ISEF, or similar competitions.
Strong background in applied mathematics, computer science, or engineering.

Responsibilities

Design and execute experiments in LLM context compression and mechanistic interpretability.
Train transformer models from scratch, owning data, architecture, training loops, and evaluation.
Build datasets, labeling pipelines, and evaluation infrastructure.
Research and prototype novel model architectures and training methods.
Deploy successful models into production to improve customer outcomes.
Read and reproduce current AI research while driving independent research initiatives.