MLOps Architect: Scalable AI Pipelines & Serving

Evlo AI; Chicago (IL); On-site; USD 120,000 - 180,000; Full time

Job summary

Evlo AI is seeking an experienced MLOps/ML engineering professional to own end-to-end ML pipelines, training, and deployment. You will build scalable serving, implement robust CI/CD, and oversee observability for production models.

You will collaborate with data scientists to translate experimental code into robust systems, optimize GPU and cloud resources, and ensure reliability with SLOs and postmortems. This role is based in Chicago for on-site operations.

Qualifications

• 3–6 years of experience in MLOps, ML engineering, or backend/platform engineering with production ML systems.
• Strong Python skills plus hands-on experience with containerization and orchestration (Docker, Kubernetes).
• Proficiency with at least one ML pipeline/workflow tool: Kubeflow, MLflow, Airflow, or SageMaker Pipelines.

Responsibilities

• Design and maintain end-to-end ML pipelines for training, validation, and deployment.
• Build and scale model serving infrastructure with Docker, Kubernetes, and frameworks like KServe, Seldon, or Triton.
• Implement CI/CD for ML systems — automated testing, model versioning, canary deployments, and rollback strategies.
• Establish monitoring and observability for production models: data drift detection, latency/throughput dashboards, and automated alerting with Prometheus and Grafana.
• Manage GPU compute and cloud resources across AWS, GCP, or Azure, optimizing cost and utilization for training and inference workloads.
• Collaborate with data scientists to productionize models, translating experimental code into robust, tested engineering systems.
• Drive platform reliability standards: SLOs, incident response, and postmortems for ML serving infrastructure.

Skills

MLOps

Python

Docker/Kubernetes

CI/CD for ML

Cloud platforms

Monitoring

Education

BSc in CS/Engineering

Tools

Docker

Kubernetes

Kubeflow

MLflow

Airflow

SageMaker Pipelines

Terraform

Prometheus

Grafana

Feast

Tecton

Kafka

Flink

vLLM

TensorRT-LLM

Triton

Job description

Evlo AI is seeking an experienced MLOps/ML engineering professional to own end-to-end ML pipelines, training, and deployment. You will build scalable serving, implement robust CI/CD, and oversee observability for production models.

You will collaborate with data scientists to translate experimental code into robust systems, optimize GPU and cloud resources, and ensure reliability with SLOs and postmortems. This role is based in Chicago for on-site operations.