Machine Learning Engineer - Expert - AI TrainerMercor • San Francisco, California, United States
Machine Learning Engineer - Expert - AI Trainer
Mercor
- San Francisco, California, United States
- San Francisco, California, United States
About
connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include
Benchmark ,
General Catalyst ,
Peter Thiel ,
Adam D'Angelo ,
Larry Summers , and
Jack Dorsey . Position:
Machine Learning Engineer Expert Type:
Contract Compensation:
$90/hour Location:
Remote Role Responsibilities Develop end-to-end
machine learning
solutions for challenging prediction and modeling problems. Analyze datasets and define appropriate modeling approaches, validation strategies, and evaluation metrics. Perform exploratory data analysis, feature engineering, and data preprocessing. Train, tune, and evaluate
machine learning models
across tabular, text, image, and time-series datasets. Review and validate the technical quality of
machine learning
projects and deliverables. Identify opportunities to improve model performance through systematic experimentation and iteration. Qualifications Must-Have Master's degree
or
PhD
in
Computer Science ,
Machine Learning ,
Statistics ,
Mathematics ,
Electrical Engineering , or a related field from a top-tier university. 2+ years
of professional experience in
machine learning , applied
AI , data science, or a closely related field. Strong proficiency in
Python
and modern
machine learning frameworks
(e.g.,
scikit-learn ,
XGBoost ,
LightGBM ,
PyTorch ,
TensorFlow ). Demonstrated experience building end-to-end
machine learning
solutions, including data preparation, model development, validation, and evaluation. Strong understanding of model evaluation metrics, validation methodologies, and experimental design. Experience with one or more of the following areas: tabular
machine learning , natural language processing, computer vision, recommendation systems, ranking systems, time-series forecasting. Ability to work independently on open-ended
machine learning
problems and deliver high-quality technical outputs. Preferred PhD
from a leading research university. Experience at leading technology companies,
AI
labs, research institutions, or high-growth startups. Participation in competitive
machine learning
or data science competitions. Experience optimizing models against performance-based evaluation metrics. Familiarity with advanced techniques such as ensembling, hyperparameter optimization, transfer learning, foundation model fine-tuning, or reinforcement learning. Publications, patents, or significant open-source contributions in
machine learning
or
AI . Experience reviewing, mentoring, or evaluating the work of other
machine learning
practitioners. Application Process (Takes 20–30 mins to complete) Upload resume AI interview based on your resume Submit form Resources & Support For details about the interview process and platform information, please check: welcome For any help or support, reach out to: PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
#hiringmercor
Languages
- English
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