Machine Learning Engineer – ML Evaluation & Experiment Design

Anyone AI is recruiting experienced Machine Learning Engineers for a specialized project focused on reviewing and evaluating machine learning challenges used in AI model training and evaluation.

The work involves analyzing ML experiments, datasets, metrics, and pipelines to determine whether challenges are technically sound, reproducible, appropriately difficult, and genuinely require strong machine learning reasoning.

What You’ll Work On

You’ll review ML challenges involving:

Experiment design and model selection

Small and synthetic datasets

Data quality and preprocessing

Distribution shift and data contamination

Label noise and feature leakage

Model evaluation and metric selection

Hyperparameter tuning

Train / validation / test methodology

Reproducibility and deterministic pipelines

Statistical significance of model improvements

A key part of the role is determining whether a challenge actually rewards good ML reasoning, rather than simply being solvable through brute-force model selection or large hyperparameter searches.

What We’re Looking For

3+ years of hands-on applied machine learning experience

Strong experience with:

ML experiment design

Model selection

Model evaluation

Data preprocessing and validation

Strong understanding of train, validation, and test splits

Ability to identify:

Data leakage

Label noise

Distribution shift

Spurious correlations

Feature leakage

Data contamination