R Engineer
ai trainerNew York (NY)
$55/hour
ApplyAbout the role
Pay: up to $55/hour
As a remote, hourly paid R Engineer, you will review AI-generated responses and generate high-quality R and data-analysis-focused content, evaluating the reasoning quality and step-by-step problem-solving behind each solution. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify errors in statistical methodology or data-wrangling workflows; fact-check analytical results; write expert-level explanations and model solutions that demonstrate correct use of R; and rate and compare multiple AI responses based on correctness and reasoning quality. This contract role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate that provides AI training data for many of the world’s largest AI companies and foundation model labs, directly helping to improve the world’s premier AI models.
Important:
There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.
Responsibilities:
Develop AI Training Content: Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects.
Optimize AI Performance: Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance.
Ensure Model Integrity: Test AI models for potential inaccuracies or biases, validating their reliability across use cases.
Requirements:
2+ years of hands‑on experience using R for data analysis, statistics, or data science work.
Strong proficiency in R programming, including data wrangling, functional programming patterns, and writing reusable functions or packages.
Solid grounding in applied statistics, including regression, inference, and model validation, with practical experience implementing these methods in R.
Experience building end-to-end analyses in R that include data cleaning, exploratory analysis, modeling, and visualization.
Familiarity with common R ecosystems such as tidyverse, data.table, and ggplot2, and the ability to choose appropriate tools for a given task.
Professional experience in a data-focused role such as data scientist, statistician, quantitative analyst, or similar.
Minimum Bachelor’s degree in Statistics, Mathematics, Computer Science, or a closely related quantitative field.
Significant experience using large language models (LLMs) to assist with coding, analysis design, and code review in R.
Excellent English writing skills with the ability to document analyses and explain complex statistical ideas clearly to non-experts.
Previous experience with AI data training or model evaluation is strongly preferred, and Minimum C1 English proficiency is required.
Skills:
Statistical Modeling, LLM coding, R programming, Data Visualization, Reproducible Research, Data Cleaning, Time Series Analysis, Machine learning in R, English, Data Analysis
Open to candidates in: Bangladesh, Bhutan, Brazil, Cambodia, Germany, India, Indonesia, Malaysia, Nepal, Pakistan, Singapore, Sri Lanka, Thailand, The Philippines, The United States, Timor Leste, Vietnam
Interview language: English
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
More like this