Senior/Staff MLOps Engineer: Scale Production ML

PathAI; Boston (MA); Hybrid; USD 128,000 - 196,000; Full time

Job summary

PathAI is seeking an experienced Senior Software Engineer (MLOps) to design, build, and scale machine learning infrastructure powering enterprise AI systems in a hybrid Boston-based role. You will architect infrastructure in AWS and on-prem, drive architectural decisions, and mentor engineers to deliver reliable ML workflows.

The role emphasizes collaboration across ML, data science, product engineering, and infrastructure teams, with a focus on deployment, monitoring, and security/compliance in

Qualifications

• BS or MS in CS/CE/SE.
• 5+ years of software engineering experience for Senior or 8+ years for Staff.
• Strong software engineering in complex, multi-language systems and scalable backend architecture.
• Experience with Kubernetes and cloud platforms (AWS preferred).
• Experience with observability and monitoring tools (Prometheus, Grafana, Datadog).
• Solid understanding of DevOps and infrastructure-as-code (Helm, Terraform).
• Experience owning development platforms and serving internal customers.
• Proficiency in Python with exposure to additional languages.

Responsibilities

• Design, develop, and scale ML infrastructure powering enterprise AI systems.
• Architect and lead ML/DevOps pipeline and deployment automation (CI/CD for ML).
• Lead architectural discussions for MLOps suite ensuring performance, security, and compliance.
• Collaborate with ML engineers, data scientists, and infrastructure teams to bridge research and production.
• Mentor junior engineers and enforce coding standards.

Skills

Python

Kubernetes

AWS

Multi-language systems

Observability tools

DevOps / IaC

Development platforms ownership

Communication

Education

BS or MS in CS/CE/SE

Tools

Prometheus

Grafana

Datadog

Helm

Terraform

Airflow

Kubeflow

Kafka

Spark Streaming

Job description

PathAI is seeking an experienced Senior Software Engineer (MLOps) to design, build, and scale machine learning infrastructure powering enterprise AI systems in a hybrid Boston-based role. You will architect infrastructure in AWS and on-prem, drive architectural decisions, and mentor engineers to deliver reliable ML workflows.

The role emphasizes collaboration across ML, data science, product engineering, and infrastructure teams, with a focus on deployment, monitoring, and security/compliance in