LLM Research Scientist (Pre-training & Post-Training)

Location: Remote

Engagement Type: Hourly Contract

Compensation:$100–$120/hour

About the Opportunity

This opportunity is for experienced Machine Learning Researchers and LLM Research Scientists interested in contributing to advanced AI research and evaluation projects. The role focuses on training, fine-tuning, and improving large language models (LLMs), conducting empirical research, and advancing state-of-the-art foundation model capabilities.

You will work on challenging research problems spanning LLM pre-training, post-training, data curation, model evaluation, alignment, and optimization.

Responsibilities

Train transformer-based language models from scratch and fine-tune open-weight foundation models.
Design and optimize pre-training and post-training pipelines for large language models.
Construct, curate, and optimize large-scale training datasets from raw web and other data sources.
Develop data filtering, deduplication, quality classification, and curriculum learning strategies.
Diagnose and resolve optimization failures, convergence issues, and training instabilities.
Build and evaluate supervised fine-tuning (SFT), preference optimization (DPO, RLHF, RLAIF), and reward modeling pipelines.
Design evaluation benchmarks and analyze model performance using rigorous experimental methodologies.
Collaborate with AI researchers to improve model reasoning, alignment, efficiency, and overall performance.

Required Qualifications

3+ years of machine learning research experience (PhD research qualifies).
Strong expertise in one or more of the following areas:
Foundation Model Pre-training
LLM Post-Training
Large-Scale Data Curation
Reinforcement Learning for LLMs
Model Alignment and AI Safety
LLM Evaluation and Benchmark Development
Strong experience with PyTorch, JAX, TensorFlow, or similar machine learning frameworks.
Deep understanding of transformer architectures, large language models, optimization techniques, and modern deep learning methodologies.
Strong Python programming skills.
Excellent analytical, research, and scientific communication skills.
Ability to work independently in a remote research environment.

Preferred Qualifications

PhD in Computer Science, Machine Learning, Artificial Intelligence, Natural Language Processing, or a related field.
Degree from a Top-100 university, experience at a FAANG or leading AI company, or an equivalent research track record through publications or impactful open-source contributions.
Experience with:
Scaling Laws
Curriculum Learning
LLM Evaluation
Reinforcement Learning
AI Alignment
AI Safety Research
Publications in leading AI conferences or significant open-source contributions.

Compensation

Competitive compensation of $100–$120/hour.
Weekly payments.
Independent contractor engagement.

Application Process

Upload Resume
Complete an AI Interview Based on Your Resume
Submit Application

Machine Learning Research Scientist