AI Tutor, ML Engineer Specialist

Summary

Join Handshake as an AI Tutor, Machine Learning Engineer Specialist and contribute to the next generation of AI models by reviewing and refining outputs generated by cutting-edge large language models (LLMs). You will apply your expertise in machine learning, data science, and technical domains to ensure model outputs meet high standards. This role blends analytical thinking with hands-on data quality work and research-grade insight into model evaluation and improvement. This is a contract remote position with variable time commitments. The role involves evaluating AI-generated outputs, suggesting improvements, contributing to dataset curation, collaborating with AI teams, and staying updated on model behaviors. Compensation is $40-$70/hr.

Requirements

• MS or PhD in Computer Science, Machine Learning, Data Science, or a closely related technical field
• Alternatively, 3+ years of professional experience as a Machine Learning Engineer or Data Scientist at a high-caliber company (e.g., FAANG, leading startups, AI labs)
• Strong grasp of core machine learning concepts, model training workflows, and evaluation strategies
• Ability to assess complex technical information and provide constructive, detail-oriented feedback
• Excellent written communication skills—both technical and explanatory writing
• Ability to operate independently with sound judgment under ambiguous conditions
• Passion for AI development, data quality, and technological advancement
• Availability to work evenings and weekends as needed
• Ability to quickly adapt to new skills and evolving requirements
• Personal device must support Windows 10 or macOS Big Sur 11.0 or later
• Reliable access to a smartphone

Responsibilities

• Use internal tools to evaluate and critique AI-generated outputs, primarily in technical and scientific domains
• Review complex model responses and suggest improvements with a focus on clarity, correctness, and domain relevance
• Contribute to the curation and refinement of datasets used to train and fine-tune AI/ML models
• Work closely with cross-functional AI teams to identify data patterns, edge cases, and model blind spots
• Stay up-to-date on model behaviors and guidelines as they evolve, applying judgment to nuanced annotation tasks

Preferred Qualifications

• Publications in machine learning, AI, or computer science journals/conferences
• Experience working with human feedback loops in ML systems (e.g., RLHF, data annotation, model alignment)
• Teaching, mentoring, or technical writing experience in ML or related technical domains
• Exposure to generative AI applications or prompt engineering

Benefits

• Fully remote position
• $40/hr - $70/hr