remote
Principal Machine Learning Engineer, Content Safety
ML Engineer
Lead the design and deployment of advanced machine‑learning models for content safety, building scalable computer‑vision pipelines and auto‑labeling systems using Python, TensorFlow/PyTorch, and cloud services.
About the role
Key Responsibilities
- Architect and implement end‑to‑end computer‑vision pipelines that automatically label and filter unsafe content at scale.
- Design, train, and optimize deep‑learning models (CNNs, transformers) using TensorFlow and PyTorch for image and video moderation.
- Integrate ML models into backend services, ensuring low latency, high throughput, and robust monitoring.
- Collaborate with cross‑functional teams to define safety criteria, data collection strategies, and annotation workflows.
- Mentor senior engineers, establish best practices for model versioning, testing, and continuous deployment on AWS.
Requirements
- 10+ years of professional experience in machine learning, with a focus on computer vision and deep learning.
- Expertise in Python and major ML frameworks such as TensorFlow or PyTorch.
- Proven track record building scalable data pipelines and deploying models in production cloud environments (AWS, GCP, or Azure).
- Strong understanding of content safety challenges, auto‑labeling techniques, and model evaluation metrics.
- Excellent problem‑solving skills and ability to lead technical discussions across multidisciplinary teams.
Skills
pythontensorflowpytorchcomputer visiondeep learningaws