MLOps Engineer: Build Scalable Production ML Pipelines

Evlo AI; Seattle (WA); On-site; USD 140,000 - 190,000; Full time

Job summary

Evlo AI is seeking an experienced MLOps Engineer to build and operate the infrastructure that moves ML models from experimentation to reliable production systems. You will own training and inference pipelines, registries, feature workflows, deployment automation, and observability across cloud environments.

Working with ML engineers, data scientists, and platform engineers, you will improve speed and safety of model releases while maintaining latency, scalability, security, and reproducibility

Qualifications

• 3–8 years of experience in MLOps, machine learning engineering, platform engineering, DevOps, or related discipline.
• Strong Python and SQL skills, with experience building services, automation, data pipelines, and developer tooling.
• Hands‑on experience with Kubernetes, Docker, Linux, cloud infrastructure, and IaC tools such as Terraform.
• Experience deploying and operating ML models using platforms like MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML, Airflow, or Argo.
• Solid understanding of ML lifecycle management, model versioning, data lineage, reproducibility, monitoring, and rollback practices.
• Bachelor’s degree in CS/Engineering/Math or related technical field; equivalent experience considered.
• Bonus: GPU scheduling, distributed training, Ray, Spark, Feast, LLM inference, model quantization, service meshes, or real-time serving systems

Responsibilities

• Build and maintain automated CI/CD pipelines for model training, validation, packaging, and deployment.
• Design reproducible ML workflows with Kubeflow, Airflow, Argo, MLflow, or equivalent platforms.
• Deploy and scale online and batch inference services across AWS, GCP, or Azure.
• Implement model and data observability for drift, data quality, latency, and resource use using Prometheus/Grafana.
• Manage model registries, feature stores, artifacts, and IaC with Terraform/CloudFormation.
• Partner with ML and data science teams to standardize training environments and release processes.
• Strengthen production ops with automated testing, incident response, security controls, and SLAs.

Skills

Python

SQL

Kubernetes

Docker

Linux

Cloud infra

IaC (Terraform)

CI/CD

DevOps tooling

ML tooling

Education

Bachelor’s degree in CS/Engineering/Math or related field

Tools

Kubeflow

Airflow

Argo Workflows

MLflow

SageMaker

Vertex AI

Terraform

Job description

Evlo AI is seeking an experienced MLOps Engineer to build and operate the infrastructure that moves ML models from experimentation to reliable production systems. You will own training and inference pipelines, registries, feature workflows, deployment automation, and observability across cloud environments.

Working with ML engineers, data scientists, and platform engineers, you will improve speed and safety of model releases while maintaining latency, scalability, security, and reproducibility