AI Engineer – Machine Learning Systems & Cloud Infrastructure

About the role

We're looking for a skilled AI Engineer to design, build, and deploy production-grade machine learning systems at scale. This is a remote-friendly opportunity for engineers who thrive at the intersection of machine learning, cloud infrastructure, and modern DevOps practices. You'll work on real-world AI applications, helping to take models from experimentation to reliable, scalable production deployments.

What you'll do

• Design, train, and optimize machine learning models for production use cases
• Build and maintain CI/CD pipelines to automate testing, deployment, and monitoring of ML systems
• Architect and manage cloud infrastructure on AWS to support scalable ML workloads
• Deploy, orchestrate, and manage containerized applications using Kubernetes
• Collaborate with cross-functional teams to translate business requirements into robust AI solutions
• Monitor model performance in production and iterate to improve accuracy, latency, and reliability
• Implement best practices for reproducibility, versioning, and observability across the ML lifecycle
• Troubleshoot and resolve issues across the model training, deployment, and serving stack

Requirements

• Proven experience building and deploying machine learning models in production environments
• Strong hands-on experience with AWS cloud services
• Practical knowledge of Kubernetes for container orchestration
• Experience designing and maintaining CI/CD pipelines for ML or software systems
• Solid understanding of software engineering fundamentals and best practices
• Ability to work independently in a remote, distributed team environment
• Strong communication skills and comfort working across time zones

**Nice to have:**

• Experience with MLOps tooling (MLflow, Kubeflow, SageMaker, etc.)
• Familiarity with infrastructure-as-code tools (Terraform, CloudFormation)
• Background in scaling deep learning or NLP models
• Experience with monitoring/observability tools for ML systems

Compensation

This role offers a competitive hourly rate of **$30–$90/hour**, based on experience and demonstrated expertise. Engagement terms are flexible, and this position is open to qualified professionals globally.