ML Engineer Specialist - Freelance AI Trainer Project

Role overview

Tackle applied machine learning challenges and help evaluate and improve AI systems through model testing, benchmark development, and structured feedback. The work spans experimentation, scientific writing review, and investigation of model reasoning across machine learning and natural language processing topics.

Responsibilities

- Develop and refine solutions to applied ML problems, from baseline approaches to optimized workflows. - Compare research abstracts and introductions against review criteria for clarity, correctness, and impact. - Probe model behavior on topics such as optimization, fairness, regularization, transformers, and applied NLP; document failure patterns. - Create benchmark tasks by finding datasets, reviewing research, writing evaluation scripts, and providing reference implementations. - Give structured feedback to improve training data and model outputs.

Requirements

- Strong background in machine learning, NLP, or data science. - Experience with supervised and unsupervised learning, deep learning, reinforcement learning, probabilistic modeling, and applied NLP. - Proficiency in Python, machine learning frameworks, and cloud-based workflows. - Clear communication skills and the ability to explain reasoning and show work.

Nice to have

- A master’s or PhD in computer science, machine learning, or data science. - Peer-reviewed research or experience building production machine learning systems.

Benefits and work setup

- Remote contract work with schedule flexibility. - Listed pay range is $30–$50 per hour; the final rate depends on experience, expertise, and location. Contractors provide a secure computer and high-speed internet. Health insurance and paid time off are not provided.