About the job
About SewerAI Corporation
SewerAI Corporation develops AI-powered solutions for underground infrastructure management. The platform helps contractors, engineering firms, and utilities turn sewer inspection data into actionable insights, reducing the need for manual video review. After doubling its customer base in the past year, SewerAI is entering a period of strong growth.
Role Overview: MLOps Engineer (AI)
This fully remote role focuses on building and maintaining the machine learning operations that power SewerAI’s products. The MLOps Engineer will design, improve, and scale the systems supporting machine learning models used for sewer and underground infrastructure assessment.
The position bridges research and production, ensuring that models move smoothly from development into reliable, high-performing deployment. Responsibilities include managing training and inference pipelines, strengthening cloud infrastructure, and developing CI/CD processes that keep models secure and dependable for defect detection and maintenance tasks.
Key Responsibilities
- Cloud Infrastructure: Audit, secure, and optimize AWS environments to support both training and production workloads with high availability and fault tolerance.
- Model Deployment & Inference: Build and maintain scalable systems for serving deep learning models (using PyTorch and TensorFlow), tuned for low latency and high throughput on complex infrastructure data.
- CI/CD for Machine Learning: Develop automated pipelines for model testing, validation, deployment, and rollback.
- Training Infrastructure: Create efficient compute environments for training computer vision and time-series models on large datasets.
- Monitoring & Observability: Set up monitoring for model drift, data quality, and system health to quickly identify and address performance issues.

