Work within a cross-functional data team to build scalable NLP and ML models
Work from end-to-end on live production pipelines. Not just modeling, not theoretical
Define the best approach to solve problems with ML. Build data and model pipelines
Test, validate, deploy, and monitor solutions for impact
Optimize models for production throughput and uptime requirements
Automate deployments, testing, and monitoring (MLOps)

🎯 Requirements

2+ years hands-on ML Engineer or Algorithm Engineer experience
Expert Python for production ML code
Strong ML concepts: training, evaluation, optimization
Practical DL/ML framework experience (PyTorch, TensorFlow)
MLOps familiarity: MLflow, Kubeflow, or AWS SageMaker
Strong problem-solving and communication

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