AI Research Scientist; Remote

This opportunity is for experienced Machine Learning Engineers with expertise in Python, machine learning, data analysis, model development, and MongoDB to contribute to advanced AI training and evaluation projects
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You’ll apply your technical expertise to design and refine machine learning solutions, analyze datasets, evaluate model performance, and develop reliable workflows that support the training and deployment of next-generation AI systems
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• Design, develop, and refine machine learning models using Python and relevant ML frameworks.
• Analyze and process large datasets for model training, validation, and evaluation.
• Use MongoDB for efficient data storage, manipulation, querying, and retrieval.
• Develop and maintain data preprocessing and feature engineering pipelines
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• Evaluate model performance using appropriate metrics, benchmarking, and validation techniques
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• Perform hyperparameter tuning and iterative model optimization.
• Collaborate with cross-functional teams to identify opportunities for model and workflow improvements
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• Integrate data pipelines into training and inference workflows
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• Document experiments, methodologies, results, and technical decisions to ensure reproducibility
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• Provide actionable insights and recommendations based on machine learning and data-driven findings
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• Professional experience working as a Machine Learning Engineer, ML Developer, Data Scientist, or similar role
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• Strong proficiency in Python and machine learning development.
• Hands‑on experience with machine learning frameworks such as scikit-learn, Tensor Flow, or Py Torch .
• Practical experience using MongoDB for data management and retrieval.
• Strong understanding of machine learning algorithms, model evaluation, and data preprocessing
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• Experience with feature engineering, hyperparameter tuning, and model benchmarking
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• Strong analytical and problem‑solving abilities.
• Excellent written communication and technical documentation skills.
• Ability to work independently and collaborate effectively in a remote environment
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• Experience deploying or operationalizing machine learning models in cloud or enterprise environments.
• Familiarity with ML pipelines, model serving, and inference workflows
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• Experience working with large-scale datasets and production ML systems.
• Knowledge of MLOps, model monitoring, or automated ML workflows
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• Experience contributing to AI training, model evaluation, or data-quality initiatives
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• Strong understanding of scalable data and machine learning architectures.
• Ability to adapt quickly to evolving technical requirements and project priorities.

• Competitive compensation of $80-$140/hour.
• Hourly contract engagement.
• Fully remote with flexible working arrangements.
• Opportunity to contribute to next‑generation AI training and evaluation projects
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