MLOps Engineer

MLOps Engineer

Location: Ukraine (Remote within Ukraine)

Company: Grid Dynamics

English: B2

At Grid Dynamics, we're looking for an experienced MLOps Engineer to join an innovative team working at the intersection of Artificial Intelligence, Robotics, and Computer Vision.

You'll help build and scale an advanced Physical AI platform, bringing machine learning models from experimentation to real-world robotic systems.

This is an opportunity to work with cutting-edge AI technologies, GPU-accelerated inference, and cloud infrastructure while solving challenging engineering problems.

💻 What You'll Do

• Build and maintain MLOps infrastructure supporting AI-powered robotic systems.
• Deploy and optimize ML models for GPU-accelerated inference using NVIDIA Triton.
• Develop scalable training, fine-tuning, and deployment pipelines.
• Implement CI/CD workflows and infrastructure automation.
• Manage ML experiments, datasets, and model versions.
• Optimize cloud infrastructure performance and costs across AWS/GCP.
• Collaborate with ML researchers, Data Scientists, and Robotics Engineers to bring models into production.

🔍 What We're Looking For

• 5+ years of experience
• Hands-on experience with MLOps and production ML deployments.
• Strong Python skills.
• Experience with Docker, Terraform, and GitHub Actions.
• Practical experience with NVIDIA Triton and GPU-based model serving.
• Familiarity with MLflow, DVC, and Kubeflow.
• Experience with AWS and/or GCP.
• Understanding of CI/CD, Infrastructure as Code, and ML lifecycle management.
• Experience with cloud-based training and fine-tuning pipelines.
• English: B2 or higher.

Nice to Have:

• Experience with Edge AI, robotics, or deploying models to edge devices.

Your Team

You'll join a collaborative, cross-functional team of 8–10 engineers, including Robotics, Computer Vision, Data Science, MLOps, Backend, and UI specialists.

The team values innovation, engineering ownership, and turning ambitious AI ideas into real-world solutions.

Why Join?

• Work on innovative Physical AI and Robotics solutions.
• Solve complex challenges involving production ML and GPU infrastructure.
• Collaborate with engineers across multiple AI disciplines.
• Make a direct impact on intelligent systems operating in the real world.