Develop, train, and evaluate ML models, with a focus on tabular, predictive, and ranking models
Work with data across the full funnel to support performance and optimization use cases
Contribute directly to production-focused modeling, ensuring models are practical, scalable, and reliable in real-world use

Bachelor’s degree in Machine Learning, Statistics, Computer Science, or a related field
3+ years of experience developing ML models for tabular data, with strong understanding of underlying methodologies
Proven experience owning ML projects end-to-end — from research to production
Proven ability to extract predictive signal from complex, messy real-world data at scale
Experience training models on Big Data and optimizing for inference latency
Hands-on experience with cloud-based ML platforms and MLOps practices (experiment tracking, model versioning, CI/CD, deployment pipelines)
Strong Python skills and solid experience with tabular ML libraries (scikit-learn, PyTorch, pandas, polars, etc.)
Solid understanding of experimental design, causality, and robust model validation techniques
Experience working closely with data engineering pipelines

Newxel

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