MLOps Engineer – Hourly and Full time

Siteup

Senior ML Engineer guiding ML pipelines and model serving infrastructure for an international client. Strong data engineering foundation and hands-on MLOps experience required.

Posted 5/25/2026full-timeRemote • Washington • 🇺🇸 United StatesSeniorLeadWebsite

Tech Stack

Tools & technologies

AirflowAWSAzureCloudDockerGoogle Cloud PlatformKubernetesPythonSpark

About the role

Key responsibilities & impact

Design and maintain end-to-end ML pipelines from data ingestion to model deployment
Operate model registries, feature stores, and experiment tracking (MLflow, W&B)
Build scalable model serving infrastructure on Kubernetes and cloud platforms
Implement CI/CD workflows for ML models, including testing and rollback strategies
Monitor production models — drift detection, alerting, and retraining pipelines
Collaborate with data scientists and platform engineers to ship ML solutions faster

Requirements

What you’ll need

5+ years in data engineering (pipelines, warehouses, orchestration)
2+ years of hands-on ML engineering / MLOps in production environments
Strong Python skills and experience with Airflow, Spark, or similar orchestration tools
Solid knowledge of Kubernetes, Docker, and at least one major cloud (AWS, GCP or Azure)
Familiarity with ML tooling: MLflow, W&B, DVC, or equivalent
Available full-time (80h/week), EST-aligned, eligible to contract in Canada (CAD)

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account Siteup Website LinkedIn All Job Openings 1 - 10 employees Founded 2024 Elevate your online presence with our innovative web and app development solutions and strategic digital marketing services. At SiteUp, we specialize in crafting custom websites and mobile apps that engage users and drive business growth. Explore our services and unleash the full potential of your digital presence today. MLOps Engineer – Hourly and Full time Job not on LinkedIn 🔥 1 minute ago ☕ Washington – Remote ⏰ Full Time 🟠 Senior 🔴 Lead 🤖 Machine Learning Engineer Airflow AWS Azure Cloud Docker Google Cloud Platform Kubernetes Python Spark Apply Now Find Hiring Managers Customize resume + cover letter Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 Description
Design and maintain end-to-end ML pipelines from data ingestion to model deployment
Operate model registries, feature stores, and experiment tracking (MLflow, W&B)
Build scalable model serving infrastructure on Kubernetes and cloud platforms
Implement CI/CD workflows for ML models, including testing and rollback strategies
Monitor production models — drift detection, alerting, and retraining pipelines
Collaborate with data scientists and platform engineers to ship ML solutions faster 🎯 Requirements
5+ years in data engineering (pipelines, warehouses, orchestration)
2+ years of hands-on ML engineering / MLOps in production environments
Strong Python skills and experience with Airflow, Spark, or similar orchestration tools
Solid knowledge of Kubernetes, Docker, and at least one major cloud (AWS, GCP or Azure)
Familiarity with ML tooling: MLflow, W&B, DVC, or equivalent
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Hard Skills & Tools

machine learningdata engineeringML pipelinesCI/CD workflowsPythonKubernetesDockerAirflowSparkmodel deployment

Soft Skills

collaborationcommunication