Analyze machine learning benchmarks, model outputs, datasets, and evaluation metrics as an intermediate contractor. Use Python, SQL, and statistical reasoning in a flexible, remote role requiring 20+ hours per week.
General Annotation
Remote
10 countries
Eligibility
Intermediate
Experience
Jul 16, 2026
Posted
Open to applicants in
India Pakistan Nigeria Kenya Egypt Ghana Bangladesh Türkiye Brazil Mexico
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OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. It helps contributors discover projects across the industry, build a professional profile, and apply in minutes.
As an OpenTrain AI contractor, you can develop a lasting portfolio of work that demonstrates your experience with machine learning evaluation and analytical workflows.
About AI Training and Evaluation Work
AI systems improve through carefully prepared data, human review, and measurable evaluation. Contributors help assess how models behave by analyzing outputs, checking data quality, investigating edge cases, and validating the metrics used to compare performance.
This work offers a way to contribute to cutting-edge AI development remotely, with flexible opportunities that can fit around other commitments.
The Role
OpenTrain AI is recruiting an MLE Bench Data Analyst for benchmark-driven evaluation work involving real-world machine learning systems. You will analyze structured and unstructured datasets from machine learning training, inference, and evaluation pipelines.
The role combines data analysis, metric validation, model-output investigation, and clear technical documentation. You will support reproducible evaluation workflows and collaborate on challenging benchmark scenarios.
Role level: Intermediate
Engagement: Contractor and part-time
Time commitment: 20+ hours per week
Eligible locations: India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Türkiye, Brazil, and Mexico
Working language: English
What You'll Do
Your work will focus on turning complex benchmark and model data into reliable analytical findings. You will help ensure that evaluation results are consistent, interpretable, and supported by well-documented analysis.
Analyze production-like datasets and machine learning outputs used in benchmark evaluation
Define, compute, and validate metrics for model performance and behavior
Investigate data distributions, failure modes, and edge cases in benchmark tasks
Write Python and SQL analyses using relational and analytical datasets
Create documented, reproducible analytical reports and artifacts
Validate consistency and correctness across datasets and experiments
Collaborate with machine learning engineers and researchers on challenging evaluation scenarios
Requirements
This role is suited to an experienced data analyst or analytics-focused engineer who can work independently with complex datasets and communicate findings clearly. Strong analytical judgment and attention to detail are important when evaluating model behavior and benchmark results.
3+ years of experience as a data analyst or analytics-focused engineer
Strong Python and SQL skills for analytical work with relational and analytical datasets
Experience analyzing machine learning outputs and evaluation metrics
Experience defining and validating machine learning evaluation metrics
Strong statistics and analytical reasoning skills
Ability to work with large, complex datasets
Comfort investigating model outputs, failure modes, and edge cases
Excellent spoken and written English communication skills
Ability to produce clear, well-documented analytical code
Why Build Your AI Training Career with OpenTrain
AI training and data labeling are the human side of building artificial intelligence. By analyzing model behavior and validating evaluation data, you help shape how modern AI systems are measured and improved.
OpenTrain gives you a place to build a profile around your skills and experience, discover projects aligned with your background, and grow a credible portfolio in a rapidly expanding field.
Remote work with a flexible part-time structure
Opportunities to apply data analysis and machine learning evaluation skills
A profile designed to showcase your AI training experience
Practical experience supporting reproducible model evaluation workflows
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