Senior AI/ML Platform Engineer

Horizontal Talent; Minneapolis (MN); On-site; USD 95,000 - 147,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

Retirement plan

Job summary

Horizontal is seeking a Senior Consultant, AI/ML Engineer to operationalize machine learning across a dynamic, mission-driven environment. In this hands‑on role, you will build and support the infrastructure, pipelines, and production practices that move models from experimentation to reliable real-world use.

Responsibilities include designing SageMaker-based platforms, using Terraform for AWS, and building CI/CD pipelines with strong security practices.

Qualifications

• 5+ years in MLOps, ML platform engineering, or ML infra with production ownership.
• Strong AWS expertise with SageMaker, S3, IAM, CloudWatch.
• Hands-on Terraform and Git-based DevOps workflows.
• Experience building CI/CD pipelines (GitLab/GitHub Actions).
• Advanced Python for production ML tooling.
• Knowledge of model monitoring and drift detection.
• Security best practices: least privilege, encryption, secrets.

Responsibilities

• Own end-to-end ML lifecycle: training pipelines, registry, versioning, deployment.
• Design SageMaker-based training/inference platforms for production-grade services.
• Implement IaC with Terraform for AWS services.
• Build CI/CD pipelines with automated tests and validations.
• Maintain consistent training/serving feature engineering.
• Set up monitoring, alerts, dashboards for model health.
• Ensure secure, scalable ML ops with proper access controls.
• Collaborate with data scientists to productionize models.
• Support Bedrock-based workflows for batch/real-time use cases.
• Improve incident response through automation and anomaly detection.

Skills

MLOps

AWS expertise

Python

CI/CD

Cross-functional collaboration

Production ownership

Tools

SageMaker

Terraform

GitLab CI

GitHub Actions

CloudWatch

Lambda

KMS

Job description

Horizontal is seeking a Senior Consultant, AI/ML Engineer to operationalize machine learning across a dynamic, mission-driven environment. In this hands‑on role, you will build and support the infrastructure, pipelines, and production practices that move models from experimentation to reliable real-world use.

Responsibilities include designing SageMaker-based platforms, using Terraform for AWS, and building CI/CD pipelines with strong security practices.