ML infra: build platform for model lifecycle (feature engineering, deployment, monitoring).
Data analysis and feature engineering for multiple use cases.
Model training for batch and real-time predictions.
Production ops: debugging, performance, and optimization on large clusters.
Collaborate with product managers, data scientists, and engineers.

🎯 Requirements

Bachelor's/Master's/PhD in CS, Statistics, or related field.
10+ years of total experience in applied ML.
Strong coding in Spark, Python, Java.
Experience with real-time evaluation and low latency.
Familiarity with Spark-MLlib, TensorFlow, and distributed ML.

🎁 Benefits

Global access to mental health and financial wellness support.
Healthcare, life, disability, and retirement options.
Paid time off for vacation and personal reasons.

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