Senior MLOps Engineer — Edge & Cloud Inference

Grid Dynamics; Województwo mazowieckie; On-site; PLN 300,000 - 460,000; Full time

Benefits offered by this job

Flexible schedule

Competitive salary

Benefits package - medical insurance,

Sports program

Corporate social events

Professional development opportunities

Well-equipped office

Job summary

Grid Dynamics seeks a Senior MLOps Engineer to design, build, and operate the ML platform powering inference for a fleet of production robots. You will optimize GPU serving with Triton and own the release lifecycle from IaC to CI/CD, while scaling training pipelines across AWS/GCP.

Collaborate with researchers and robotics engineers to bridge prototype and scalable production. You will manage datasets, model registries, and experiment tracking (MLflow, DVC, Kubeflow), and drive cloud cost

Qualifications

• Solid foundation in MLOps, taking models from training to production deployment.
• Proficiency in Python, plus Docker, Terraform, and GitHub Actions.
• Experience serving ML models on GPUs using NVIDIA Triton and managing ML lifecycle tooling (MLflow, DVC).
• Hands-on with AWS and/or GCP, including autoscaling and spot/preemptible instances.

Responsibilities

• Build and maintain the ML platform powering inference across production robots.
• Deploy and optimize models on GPUs using NVIDIA Triton for fast, cost-efficient inference.
• Own end-to-end release lifecycle for ML workloads: IaC (Terraform) and CI/CD (GitHub Actions).
• Develop scalable training and fine-tuning pipelines on cloud infrastructure (AWS/GCP).
• Manage datasets, model registries, and experiment tracking (DVC, MLflow, Kubeflow).
• Control cloud costs across AWS and GCP with smart scaling.
• Create internal tools/libraries to help data scientists ship models smoothly.
• Collaborate with ML researchers, CV engineers, and robotics teams to move prototypes to production.

Skills

MLOps experience

Python

CI/CD understanding

Cloud cost optimization

Tools

Docker

Terraform

GitHub Actions

NVIDIA Triton

MLflow

DVC

Kubeflow Pipelines

Job description

Grid Dynamics seeks a Senior MLOps Engineer to design, build, and operate the ML platform powering inference for a fleet of production robots. You will optimize GPU serving with Triton and own the release lifecycle from IaC to CI/CD, while scaling training pipelines across AWS/GCP.

Collaborate with researchers and robotics engineers to bridge prototype and scalable production. You will manage datasets, model registries, and experiment tracking (MLflow, DVC, Kubeflow), and drive cloud cost