Join a forward-thinking team building advanced ML systems! We are looking for an experienced DevOps Engineer to support the development, training, and deployment of machine learning models in production environments.

What You’ll Do:

• Build and maintain MLOps infrastructure supporting the full ML lifecycle: model training, validation, deployment, and quality monitoring

• Develop data processing pipelines, particularly for image datasets

• Collaborate with ML and software engineering teams to ensure high-quality, efficient, and maintainable code

• Automate CI/CD processes and manage containerized applications (Docker, Kubernetes)

• Deploy and monitor ML models in production

What We Expect:

• Several years of experience in DevOps or a similar role

• Excellent Python skills (required)

• Experience building ML systems (not hosted LLMs) with frameworks such as PyTorch, TensorFlow, JAX

• Knowledge of MLOps tools (W&B, MLFlow)

• Strong software engineering practices: writing high-performance, modern, bug-free code, proper documentation, unit testing, and code quality management

• Good working knowledge of Linux environments, Git workflows, and GitHub Actions

• Experience with cloud computing, particularly AWS (preferred)

• Experience with deep learning frameworks (PyTorch, PyTorch Lightning, etc.) is a plus