Machine Learning Engineer

🔥 10 minutes ago

🗽 New York – Remote

🗽 New York – Remote

💵 $60 - $80 / hour

⏱ Part Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 0%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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24-MAG

WebsiteLinkedInAll Job Openings

2 - 10 employees

🤝 B2B

💼 Consulting

B2B • Consulting

24-MAG is a commercial strategy and execution firm that helps B2B organizations design and implement systems, workflows, and operating rhythms for sales, client management, and cross-functional projects. They focus on transforming scattered processes into aligned, measurable, and scalable commercial functions—covering pipeline structure, account management frameworks, and operational discipline for teams seeking efficient, intentional growth.

📋 Description

• Evaluate applied machine learning experiments for methodological soundness • Review experimental hypotheses, assumptions, modelling choices, and supporting rationale • Assess train/test splits, cross-validation strategies, validation procedures, datasets, and experimental protocols • Identify data leakage, target leakage, contamination, metric gaming, overfitting, cherry-picking, and unreliable conclusions • Review model-selection decisions, hyperparameter-tuning approaches, model comparisons, metrics, and statistical evidence • Reproduce or validate experimental results and diagnose discrepancies • Review code, configuration, experimental settings, and supporting evidence • Work with PyTorch, TensorFlow, scikit-learn, and XGBoost implementations • Review applied ML tasks and benchmark-style challenges • Assess assigned ML tasks against structured technical criteria • Provide clear written explanations and precise technical feedback supporting evaluation decisions • Distinguish genuine methodological problems from reasonable alternative approaches

🎯 Requirements

• 3+ years of hands-on applied or experimental machine learning experience • Strong practical experience with experiment design, model selection, hyperparameter tuning, and evaluation methodology • Deep understanding of data leakage, metric gaming, train/test methodology, and cross-validation hygiene • Proficiency with standard ML frameworks such as PyTorch, TensorFlow, scikit-learn, or XGBoost • Strong ability to critique machine learning claims against experimental evidence • Comfortable reproducing results and diagnosing discrepancies • Strong quantitative and analytical judgement • Clear written communication and ability to provide precise technical feedback • Kaggle, ML competition, or benchmark experience is advantageous • Graduate research or publication experience in applied machine learning is preferred • Previous task-grading, technical peer-review, or ML evaluation experience is advantageous • Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party • H1-B and STEM OPT support is unavailable for this engagement

🏖️ Benefits

• Part-time independent contractor engagement • Fully remote within the United States • Flexible scheduling based on project requirements • Projects may be extended, shortened, or concluded based on project needs and performance