ML Platform Engineer: Scale Models with CI/CD Observability

Evlo AI; Boston (MA); On-site; USD 150,000 - 190,000; Full time

Job summary

Evlo AI seeks an experienced MLOps Platform Engineer to own the infrastructure turning experimental ML work into production systems. You will design and operate CI/CD pipelines, model serving, and observability for reliable, scalable ML workflows.

You will collaborate with ML engineers and data scientists to reduce friction between notebooks and production, implement IaC with Terraform or Pulumi, and optimize cloud costs while ensuring reproducibility and governance.

Qualifications

• 3–6 years of MLOps/DevOps or platform engineering experience.
• Production ML systems support with cloud infrastructure.
• Proficient Python and/or Go development for automation.
• Experience with observability tooling and IaC practices.

Responsibilities

• Design and maintain CI/CD pipelines for ML workflows.
• Build and operate model serving infrastructure on Kubernetes.
• Implement monitoring, latency, drift detection, and alerting.
• Develop feature stores and data pipeline integrations.
• Optimize training and inference costs across clouds.
• Establish MLOps best practices and infrastructure-as-code standards.
• Collaborate with ML engineers to debug production incidents.

Skills

MLOps experience

DevOps experience

Platform engineering

Education

Bachelor’s degree in Computer Science or Engineering

Tools

Kubernetes

Docker

Terraform

Pulumi

Job description

Evlo AI seeks an experienced MLOps Platform Engineer to own the infrastructure turning experimental ML work into production systems. You will design and operate CI/CD pipelines, model serving, and observability for reliable, scalable ML workflows.

You will collaborate with ML engineers and data scientists to reduce friction between notebooks and production, implement IaC with Terraform or Pulumi, and optimize cloud costs while ensuring reproducibility and governance.