AI Research Scientist (Remote | $140–$150/hr)

Synthires; California (MO); On-site; USD 193,000 - 207,000; Full time

Benefits offered by this job

Flexible hours

Asynchronous work

Remote-friendly

Job summary

Synthires is seeking experienced Machine Learning Research Experts to design benchmark tasks, evaluate model capabilities, and contribute expert-level ML reasoning to next-generation AI systems. The role is for researchers who publish, write ML code, and advance ideas across domains such as language models, deep learning, reinforcement learning, CV, and AI for science.

Flexible workload and fully asynchronous work are offered; responsibilities include grading rubrics, evaluating outputs for

Qualifications

• At least one first-author publication in ML/AI or a closely related field.
• Master's or PhD in ML, CS, statistics, mathematics, or related quantitative discipline (completed or in progress).
• Minimum 1 year of hands-on machine learning research experience.
• Strong experience developing, training, evaluating, or deploying machine learning models.
• Proficiency in machine learning programming and experimentation.
• Ability to design technically rigorous research problems and evaluation frameworks.
• Excellent written communication and technical documentation skills.

Responsibilities

• Design realistic machine learning research tasks and benchmark problems.
• Develop expert-level reference solutions and evaluation methodologies.
• Create grading rubrics that assess model reasoning, implementation quality, and scientific correctness.
• Evaluate AI-generated solutions for technical accuracy, research validity, and methodological rigor.
• Author problem sets covering advanced machine learning concepts and research workflows.
• Review model outputs and identify weaknesses in reasoning, implementation, experimentation, and interpretation.
• Document expected solutions, evaluation criteria, and benchmark standards.
• Contribute domain expertise to improve the quality of frontier AI evaluation systems.

Skills

First-author publication

ML research

Experimentation

Scientific writing

Education

Master's or PhD in ML, CS, statistics, mathematics, or related quantitative discipline

Job description

AfterQuery partners with leading AI research organizations to evaluate and improve frontier AI systems. We are seeking experienced Machine Learning Research Experts with a proven research track record to design benchmark tasks, evaluate model capabilities, and contribute expert-level ML reasoning to next-generation AI systems.

This role is intended for researchers who actively conduct machine learning research, write ML code, publish scientific work, and contribute original ideas to the field. The focus is on designing rigorous evaluation tasks that measure real-world AI capabilities across diverse machine learning domains.

Areas of interest include Language Models, Deep Learning, Reinforcement Learning, Computer Vision, Generative AI, Robotics, ML Systems, Optimization, Learning Theory, Time Series Forecasting, Causal Inference, Trustworthy AI, and AI for Science.

Key Responsibilities

• Design realistic machine learning research tasks and benchmark problems.
• Develop expert-level reference solutions and evaluation methodologies.
• Create grading rubrics that assess model reasoning, implementation quality, and scientific correctness.
• Evaluate AI-generated solutions for technical accuracy, research validity, and methodological rigor.
• Author problem sets covering advanced machine learning concepts and research workflows.
• Review model outputs and identify weaknesses in reasoning, implementation, experimentation, and interpretation.
• Document expected solutions, evaluation criteria, and benchmark standards.
• Contribute domain expertise to improve the quality of frontier AI evaluation systems.

Required Qualifications

• At least one first-author research publication in Machine Learning, Artificial Intelligence, or a closely related field.
• Master's or PhD in Machine Learning, Computer Science, Statistics, Mathematics, or a related quantitative discipline (completed or currently in progress).
• Minimum 1 year of hands‑on machine learning research experience.
• Strong experience developing, training, evaluating, or deploying machine learning models.
• Demonstrated proficiency in machine learning programming and experimentation.
• Ability to design technically rigorous research problems and evaluation frameworks.
• Excellent written communication and technical documentation skills.

Preferred Qualifications

• Multiple first-author publications.
• Publications demonstrating measurable improvements over established baselines.
• Research published at leading venues such as NeurIPS, ICML, ICLR, CVPR, ACL, EMNLP, CoRL, MLSys, or equivalent conferences and journals.
• Deep expertise in one or more specialized machine learning research areas.
• Experience creating benchmarks, evaluations, datasets, or scientific assessments.
• Strong understanding of experimental methodology, reproducibility, and model evaluation.
• Experience working on frontier AI systems, large-scale ML infrastructure, or advanced research projects.

Compensation

• $140–$150/hour
• Flexible workload (5–40 hours per week)
• Fully asynchronous work environment