Senior ML Engineer - Offline Team

Job summary

Responsibilities

We're looking for a Senior ML Engineer to join our Models team. You will be joining a dedicated squad of Data Engineers, Data Scientists, and ML Engineers focused on building and maintaining the ML training infrastructure that powers our ad-targeting models from data preprocessing through model…

• Architectural Ownership: Take end-to-end ownership of highly visible projects from ideation to production release.
• Pipeline Engineering: Build and maintain quality data and ML pipelines to align with ever-evolving business and machine learning needs.
• Data Scientists Enablement: Enable Data Scientists to iterate faster by providing reusable, well-tested pipeline components (transformers, dataloaders, training utilities) and…
• Deep Learning Development: Contribute to deep learning development: GPU workload orchestration, custom PyTorch training loops, and model architecture support.
• ML Lifecycle & Reproducibility: Maintain reproducibility and consistency across the ML lifecycle: versioned configs, experiment tracking, and online-offline consistency tooling.

What they're looking for

• 5+ years minimum of experience as an ML Engineer or a similar role
• End-to-End ML Ownership: Problem framing, baselines, experimentation, deployment, and iteration
• Python Proficiency: Extensive knowledge for ML pipeline code: preprocessing, training/evaluation workflows, experiment utilities, and reproducible configs
• Training Mechanics: Comfortable implementing training mechanics where needed (custom steps/metrics, dataloading patterns, performance-conscious preprocessing), not only…
• ML Frameworks: Practical experience training and evaluating models with scikit-learn, LightGBM, PyTorch for deep learning

Tech stack

• Transformers
• PyTorch
• Node.js
• Airflow
• dbt
• Python
• scikit-learn
• AWS