MLOps Engineer - Build Scalable AI Pipelines & Deployments

Evlo AI; Washington (District of Columbia); On-site; USD 140,000 - 210,000; Full time

Job summary

Evlo AI is seeking an MLOps Engineer to own infrastructure and automation for productionizing ML and GenAI systems. You will build repeatable pipelines for training, evaluation, deployment, monitoring, and rollback across cloud platforms.

You will collaborate with ML engineers, data scientists, and platform teams to improve model release velocity while preserving security, reproducibility, and reliability. The role spans Kubernetes, CI/CD, registries, observability, and serving systems for

Qualifications

• 3–8 years of experience in MLOps, platform engineering, DevOps, or software engineering
• Strong Python and Linux skills
• Hands-on experience with Docker, Kubernetes, infrastructure as code, and at least one major cloud platform
• Practical knowledge of ML lifecycle tooling such as MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML, Airflow, or comparable platforms
• Experience designing CI/CD pipelines and observability using Prometheus, Grafana, OpenTelemetry, ELK, or cloud-native monitoring services
• Equivalent professional experience considered when missing a degree

Responsibilities

• Build and maintain ML pipelines for data validation, feature processing, model training, evaluation, registration, and promotion
• Automate model and service deployment with Docker, Kubernetes, Helm, and Terraform across AWS, Azure, or GCP
• Develop CI/CD workflows for Python services, model artifacts, infrastructure changes, and container images
• Implement production monitoring for service health, latency, throughput, resource utilization, data drift, model performance, and quality regressions
• Operate scalable model-serving infrastructure using platforms such as KServe, Seldon, NVIDIA Triton, Ray Serve, or managed cloud endpoints
• Establish reproducibility and governance practices for datasets, features, model versions, experiments, secrets, and deployment approvals
• Troubleshoot production incidents, improve system reliability, and document runbooks, architecture decisions, and operational standards

Skills

Python

Linux

Docker

Kubernetes

Cloud platforms

ML tooling

CI/CD

Observability

Education

Bachelor's degree in CS/Engineering/Math

Tools

Kubeflow

Airflow

MLflow

SageMaker

Vertex AI

Azure ML

Job description

Evlo AI is seeking an MLOps Engineer to own infrastructure and automation for productionizing ML and GenAI systems. You will build repeatable pipelines for training, evaluation, deployment, monitoring, and rollback across cloud platforms.

You will collaborate with ML engineers, data scientists, and platform teams to improve model release velocity while preserving security, reproducibility, and reliability. The role spans Kubernetes, CI/CD, registries, observability, and serving systems for