About this opportunity
Confidential lists this Machine Learning Research Scientist for AI Research opportunity in Southwest Greensburg, Pennsylvania. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Role Overview
Shape challenging machine learning engineering plans for a long-horizon AI research project. This role focuses on proposing problems that test the limits of frontier models, with an emphasis on inference, evaluation, and systems work rather than intensive model training.
Key Responsibilities
Develop ideas for difficult machine learning engineering tasks and plans.
Design tasks that frontier models solve in no more than 2 of 8 attempts.
Focus primarily on inference, evaluation, and systems challenges. Approximately half of tasks use GPUs and half are CPU-only.
Clearly articulate why each proposed problem is difficult for a frontier model.
Contribute task ideas rather than building or reviewing the tasks.
Qualifications
Current or recent experience as an ML research engineer, research scientist, or applied scientist.
Personal hands-on experience training, fine-tuning, or optimizing models using PyTorch or JAX.
Deep expertise in at least one area: LLM pretraining, alignment, or evaluations; GPU inference and performance, including vLLM, Triton, CUDA, or profiling; reinforcement learning; or scientific ML in weather and climate, physics, or biology.
Ability to explain why a problem is challenging for a frontier model.
Preferred Qualifications
Experience writing benchmark or evaluation questions.
PhD in machine learning, computer science, or physics, or an MSc with strong research output.
Publications.
Candidate Profile
This opportunity is not intended for software or full-stack engineers whose AI experience is primarily limited to LangChain or RAG application development.
Applicants with experience limited to AI trainer, rater, or annotator work are not a fit.
Work Terms
Remote, hourly engagement.
Compensation
$150 to $200 per hour.
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.