Machine Learning Evaluator - AI Trainer

• Evaluate the quality, correctness, and methodological rigor of applied machine-learning tasks for training and evaluating models.
• Assess experiment design, model-selection reasoning, and evaluation methodology.
• Provide clear, rubric-based written feedback to improve AI model performance.
• Review and critique ML claims against evidence and reproduce results.
• Work independently and asynchronously to meet deadlines while enhancing model outputs., Principal Machine Learning Engineer to serve as a hands-on technical leader for machine learning, predictive modeling, scoring, decisioning, and applied AI initiatives. This role w…
• 1 month ago

Must-Have

• 3+ years hands-on applied/experimental ML experience.
• Strong grasp of data-quality rigor: leakage detection, metric gaming, and train/test/CV hygiene.
• Proficiency with standard ML frameworks (PyTorch, TensorFlow, scikit-learn, XGBoost).
• Ability to critique ML claims against evidence and reproduce results.

Preferred

• Competition/benchmark experience (e.g., Kaggle).
• Graduate research or publication record in applied ML.
• Prior task-grading or peer-review experience.