Sr Machine Learning Engineer - ML Data

Responsibilities: Design and develop secure, scalable backend systems for ML platforms Collaborate with ML engineers and scientists to enable model training, evaluation, deployment, and serving Build and maintain ML data infrastructure including feature stores and data pipelines Implement embedding management at scale with versioning, refresh, and retirement policies Ensure data quality, testing, and validation across ML workflows Drive automation, CI/CD, and operational reliability of ML systems Evaluate and select technologies suited to ad network challenges Contribute to privacy-preserving ML initiatives and experimentation frameworks

Key requirements: Experience writing mission-critical code for production ML systems Experience building ML infrastructure used by multiple teams Experience with feature stores or ML data infrastructure in production Embedding management experience at scale Solid understanding of ML lifecycle (training, deployment, serving) Knowledge of model evaluation, data drift, train-serve skew Experience with PyTorch or TensorFlow Experience with large-scale data generation across multi-modal data and production data pipelines Experience batch and streaming ML deployments and modern storage formats Strong data modeling and data architecture skills Strong debugging, performance tuning, and automation/CI/CD Effective communication with technical and non-technical teams Product-minded with ownership attitude collaborative mindset results-oriented strong problem-solving PyTorch TensorFlow ML infrastructure