MLOps engineer for physical AI and robotics platform

Grid Dynamics

Wrocław

On-site

PLN 180,000 - 280,000

Full time

6 days ago
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Benefits offered by this job

Конкурентная зарплата
Гибкий график
Медицинское страхование и спорт
Корпоративные соц. мероприятия
Профессиональное развитие
Хорошо оборудованный офис

Job summary

Grid Dynamics ищет ML-инженера для разработки и поддержки платформы ML и инференс пайплайнов в условиях производственных роботов. Ваша работа будет включать развёртывание моделей на GPU через Triton и управление полным жизненным циклом релизов в облачных средах AWS/GCP.

Требуется опыт переноса моделей в прод и знание Python, Docker, Terraform и GitHub Actions, а также инструментов MLflow/DVC/Kubeflow. Наличие навыков edge/робототехника будет плюсом.

Qualifications

  • Опыт вывода ML-моделей на продакшн, от обучения до развёртывания.
  • Владение Python и Docker, Terraform, GitHub Actions.
  • Опыт работы с NVIDIA Triton на GPU.
  • Опыт AWS и/или GCP, с автошкалированием GPU.
  • Знание ML lifecycle и инструментов версионирования MLflow, DVC, Kubeflow Pipelines.
  • Понимание CI/CD, IaC и тестирования ML workloads.
  • Плюсом будет edge-развертывания или робототехника.

Responsibilities

  • Разработка и поддержка ML-платформы и инференс пайплайнов.
  • Развертывание и оптимизация ML-моделей на GPU через Triton.
  • Управление полным жизненным циклом релизов ML-нагрузок (IaC, CI/CD, prod deployments).
  • Разработка масштабируемых пайплайнов обучения и тонкой настройки в AWS и GCP.
  • Управление датасетами, реестрами моделей и экспериментами.
  • Контроль затрат на облаке с использованием spot/прерываемых инстансов и авто-масштабирования GPU.
  • Разработка инструментов и внутренних библиотек для упрощения развёртывания моделей.
  • Сотрудничество с ML-исследователями и робототехническими инженерами.

Skills

Python
Docker
Terraform
GitHub Actions
NVIDIA Triton
AWS/GCP
MLflow
DVC
Kubeflow

Tools

Docker
Terraform
GitHub Actions
NVIDIA Triton
MLflow
DVC
Kubeflow

Job description

Описание:

Grid Dynamics provides technology consulting, platform and product engineering, AI, and advanced analytics services. It helps enterprise companies undergoing business transformation address technical challenges and achieve positive business outcomes. The company has extensive experience and expertise in enterprise AI, data, analytics, cloud and DevOps, application modernization, and customer experience.

Задачи:
  • Build and maintain the ML platform and inference pipelines serving models across production robots
  • Deploy and optimize ML models on GPUs using NVIDIA Triton for fast, low-latency, cost-efficient inference
  • Own the end-to-end release lifecycle for ML workloads, including Infrastructure as Code, CI/CD pipelines, and production deployments
  • Develop and execute scalable model training and fine-tuning pipelines on AWS and GCP
  • Manage datasets, model registries, and experiment tracking
  • Control cloud infrastructure costs across AWS and GCP using spot/preemptible instances and GPU autoscaling
  • Build tools and internal libraries that help data scientists and robotics engineers deploy models without handling raw infrastructure
  • Partner with ML researchers, computer vision specialists, and robotics engineers to move models from prototype to high-availability production environments
Требования:
  • Hands-on experience taking machine learning models from training through production deployment
  • Proficiency in Python and working knowledge of Docker, Terraform, and GitHub Actions
  • Experience serving and optimizing ML models on GPUs using NVIDIA Triton
  • Familiarity with ML lifecycle and versioning tools, including MLflow, DVC, and Kubeflow Pipelines
  • Hands-on experience with AWS and/or GCP, including spot/preemptible instances and GPU autoscaling
  • Understanding of CI/CD pipelines, Infrastructure as Code, and automated testing practices for ML workloads
  • Familiarity with model fine-tuning techniques and distributed training pipelines on cloud infrastructure
  • Будет плюсом: edge deployments or robotics environments, deploying computer vision models or working with Physical AI frameworks
Условия:
  • Competitive salary
  • Flexible schedule
  • Benefits package including medical insurance and sports
  • Corporate social events
  • Professional development opportunities
  • Well-equipped office
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