Senior ML Infrastructure Engineer (MLOps) — Hybrid

Innovative Signal Analysis, Inc.; Boston (MA); Hybrid; USD 153,000 - 204,000; Full time

Benefits offered by this job

Free SimpliSafe system

Total rewards package

Employee Resource Groups

Job summary

SimpliSafe in Boston is seeking an experienced ML Infrastructure/MLOps Engineer to drive the development and deployment of machine learning models. You will optimize ML workflows and ensure our infrastructure is scalable, reliable, and secure.

Join a hybrid team that values automation, cloud technology, and end-to-end ML delivery. You will build CI/CD pipelines, manage AWS-based infrastructure, and champion versioning, observability, and on-call reliability.

Qualifications

• 5+ years in software or data engineering with ML focus.
• Hands-on AWS and cloud infrastructure experience.
• Experience with CI/CD, Docker, Kubernetes, and IaC tools.
• Python programming with ML frameworks (TensorFlow, PyTorch).
• ML lifecycle management including versioning and monitoring.

Responsibilities

• Lead architecture, deployment, and optimization of scalable ML model serving systems for real-time and batch use cases.
• Collaborate with data scientists and engineers to operationalize ML models.
• Develop CI/CD pipelines for ML models enabling rapid, safe releases.
• Design production monitoring for ML models and systems.
• Manage cloud infrastructure to support ML workloads (AWS or similar).
• Drive best practices in model versioning, observability, reproducibility, deployment reliability.
• Serve in an on-call rotation for team-owned software.

Skills

Communication skills

Cross-functional collaboration

Cloud technology

CI/CD experience

Python programming

Tools

AWS

Docker

Kubernetes

Terraform

CloudFormation

CI/CD tooling

Job description

SimpliSafe in Boston is seeking an experienced ML Infrastructure/MLOps Engineer to drive the development and deployment of machine learning models. You will optimize ML workflows and ensure our infrastructure is scalable, reliable, and secure.

Join a hybrid team that values automation, cloud technology, and end-to-end ML delivery. You will build CI/CD pipelines, manage AWS-based infrastructure, and champion versioning, observability, and on-call reliability.