SewerAI Corporation - ML Ops Engineer (AI)

• Cloud Infrastructure: Deep expertise in AWS (e.g., EC2, S3, EKS, SageMaker, Lambda) and cloud security best practices. • Containerization & Orchestration: Strong experience with Docker and Kubernetes for packaging and scaling ML applications. • Infrastructure as Code (IaC): Proficiency with tools like Terraform or AWS CloudFormation. • CI/CD Pipelines: Experience building robust automated pipelines using GitHub Actions, GitLab CI, or Jenkins. • Programming: Strong Python skills with a focus on writing clean, production-grade, and well-tested code. • MLOps Frameworks: Familiarity with model registry and tracking tools (e.g., MLflow, Weights & Biases). • Experience with our specific data stack (Hex, dbt, ClickHouse, Anyscale, Ray, Deeplake). • Familiarity with deep learning frameworks (PyTorch preferred) and optimization techniques like TensorRT or ONNX. • Knowledge of edge computing or deploying models to IoT devices. • Experience in the infrastructure, utility, or geospatial domains. • 4-6+ years of experience in MLOps, DevOps, or Data Engineering, with a strong emphasis on machine learning workloads. • A security-first and stability-first mindset—you think about edge cases, failure modes, and system hardening by default. • Strong collaborative instincts to work closely with Data Scientists, ensuring smooth handoffs from experimentation to production. • Clear communication skills to articulate architectural decisions and tradeoffs to the broader technical team. • What You'll Gain • Impact: Your infrastructure will directly support systems that prevent critical failures in city utility networks. • Ownership: You will have the autonomy to shape the foundational MLOps architecture and set the standard for engineering excellence on the AI team. • Modern Stack: Work alongside highly skilled peers in a modern data and ML ecosystem.