[Hiring] ML Ops Engineer @SewerAI Corporation

Role Description

We're looking for an MLOps Engineer to own the Machine Learning Operations infrastructure that powers our AI products. In this role, you will be the architectural backbone of our machine learning systems, responsible for designing, hardening, and scaling the infrastructure that powers our applied machine learning models for underground infrastructure and sewer line analysis.

You will focus on transitioning research and development into robust, production-ready systems. This means taking ownership of our training and inference pipelines, fortifying our cloud-based architecture, and building seamless CI/CD processes to ensure our models deliver reliable, high-performing, and secure actionable insights for defect detection and infrastructure maintenance.

What You'll Work On

• Architectural Hardening:
  • Audit, secure, and optimize our existing cloud infrastructure (AWS) to ensure high availability, fault tolerance, and security for both training and production workloads.
• Model Deployment & Inference:
  • Design and maintain scalable architectures for serving deep learning models (PyTorch/TensorFlow), optimizing for low latency and high throughput in handling complex infrastructure data.
• CI/CD for Machine Learning:
  • Build and maintain automated pipelines for model testing, validation, deployment, and rollback.
• Training Infrastructure:
  • Architect efficient, scalable compute environments for training complex computer vision and time-series models on large datasets.
• Monitoring & Observability:
  • Implement comprehensive monitoring for model drift, data quality, and system health, ensuring rapid response to performance degradation.

Qualifications

• Deep expertise in AWS (e.g., EC2, S3, EKS, SageMaker, Lambda) and cloud security best practices.
• Strong experience with Docker and Kubernetes for packaging and scaling ML applications.
• Proficiency with tools like Terraform or AWS CloudFormation.
• Experience building robust automated pipelines using GitHub Actions, GitLab CI, or Jenkins.
• Strong Python skills with a focus on writing clean, production-grade, and well-tested code.
• Familiarity with model registry and tracking tools (e.g., MLflow, Weights & Biases).

Nice-to-Have Skills

• 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.

What We're Looking For

• 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

• Your infrastructure will directly support systems that prevent critical failures in city utility networks.
• You will have the autonomy to shape the foundational MLOps architecture and set the standard for engineering excellence on the AI team.
• Work alongside highly skilled peers in a modern data and ML ecosystem.

Compensation & Benefits

• Base Salary: $130,000-160,000
• Equity opportunities available
• Benefits include:
  • Medical, Dental, Vision, Basic Life, 401(k), and more
  • Unlimited PTO
  • Tools and resources to support success
  • Competitive compensation with high-growth potential

Why Join SewerAI?

Join the fastest-growing team in wastewater tech and help modernize critical infrastructure with AI. You’ll own high-visibility projects, influence how our brand meets the market, and see your work drive measurable impact for customers and communities.