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# AI/ML Engineer

- **Company:** Info Dinamica Inc
- **Location:** Atlanta, GA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Batch Processing, Continuous Integration, Distributed Systems, Python (Programming Language), Machine Learning, Cloud Services, Azure Machine Learning, Data Logging, Containerization, Kubernetes, Deployment Automation, Machine Learning Operations, Docker, Microservices
- **Published:** August 22, 2026
- **Apply:** https://www.dice.com/job-detail/c0b97abc-2f1b-41db-8eca-1262a47e2d73

## About the Role

We are looking for a skilled Machine Learning Platform Engineer to design, build, and maintain scalable ML platforms and infrastructure. The ideal candidate will have strong experience in platform engineering, microservices architecture, and deploying ML models into production environments., Experience Level: 5 10 years

Strong experience in Python (must-have)

Hands-on experience in ML Platform Engineering / ML Engineering

Solid understanding of model inferencing and deployment strategies

Experience with microservices architecture and platform development

Proficiency in Docker, containers, and Kubernetes

Good understanding of distributed systems and scalable architectures

Preferred Qualifications:

Experience working with Microsoft Azure (highly preferred)

Familiarity with Azure ML, AKS, or related cloud services

Experience with MLOps practices and tools

## Description

Design and develop robust ML platforms to support model development, training, and deployment

Build and maintain scalable microservices-based architectures for ML applications

Develop and optimize model inference pipelines for real-time and batch processing

Work with containerization technologies like Docker and orchestration tools such as Kubernetes

Collaborate with data scientists and engineers to productionize ML models

Ensure platform reliability, scalability, and performance

Implement best practices for CI/CD, monitoring, and logging in ML systems


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