Online Machine Learning Engineer Jobs (Work From Home)

Typical ranges for remote Filipino specialists, reviewed July 2026. Paid in USD, direct to you.

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• Python and ML library proficiency: Scikit-learn, PyTorch, or TensorFlow — verify production-level usage, not just familiarity; ask for a trained model they have deployed to a real inference endpoint and how it performed.
• Feature engineering and data preparation: The ability to identify and engineer predictive features from raw data is a core ML skill — ask how they approached feature selection for a past classification problem and what impact it had on model performance.
• Model evaluation and metric selection: Choosing the right evaluation metric for the business problem — accuracy is misleading for imbalanced classes; precision/recall tradeoffs matter for cost-asymmetric errors; ask how they select metrics for a new problem.
• Experiment tracking and model versioning: MLflow, Weights & Biases, or Neptune — the ability to track training runs, compare experiments, and reproduce results is essential for iterative ML development.
• Model deployment to production: Deploying a model as a REST API via FastAPI, AWS SageMaker, or Hugging Face Inference Endpoints — ask for a production deployment they built and any latency or availability issues they resolved.
• NLP and text model fine-tuning (if applicable): Fine-tuning BERT, RoBERTa, or instruction-tuned LLMs on domain-specific classification or generation tasks — ask for a fine-tuning project and the evaluation methodology they used to measure improvement.

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