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24 дня назад

Cloud Platform - Infrastructure Engineer (Robotics)

140 000 - 174 500$
Формат работы
onsite
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Cloud Platform - Infrastructure Engineer (Robotics) (Cloud Infrastructure/MLOps): Building scalable cloud, ML, ETL, and CI/CD infrastructure that transforms robot telemetry into datasets, analytics, and deployable models with an accent on self-service workflows, model lifecycle management, and fleet operations. Focus on designing checkpointing and experiment-tracking systems, automating data pipelines, deploying models to field robots, and improving platform reliability and cloud cost efficiency.

Location: Pittsburgh, PA; onsite five days a week

Salary: $140,000–$174,500 per year, plus potential equity awards and an annual performance-based bonus.

Company

hirify.global Robotics develops and deploys robots for direct-to-customer food production, with a focus on improving efficiency, quality, and customer satisfaction in the food industry.

What you will do

  • Own the cloud platform infrastructure supporting a fleet of food-production robots.
  • Design and maintain scalable ML infrastructure for storage, pipeline management, environment setup, checkpointing, metadata, and experiment tracking.
  • Build self-service ML workflows and tooling for ML engineers and data scientists.
  • Develop automated ETL and data-ingestion pipelines that transform robot telemetry into datasets for training and analytics.
  • Contribute to Terraform infrastructure-as-code and CI/CD automation for model deployment, data processing, and cloud services.
  • Partner with cloud and embedded engineers on fleet model deployment, platform observability, reliability, model-drift monitoring, and cloud-cost optimization.

Requirements

  • 3+ years of experience in cloud infrastructure, MLOps, and data engineering at scale.
  • Experience with automated model checkpointing, model registries, metadata management, and tools such as MLflow or Kubeflow.
  • Strong experience with cloud workflow orchestration tools such as Argo Workflows, Airflow, Prefect, or similar.
  • Experience with cloud storage architectures and building self-service ML platforms, pipeline abstraction layers, or automated developer workflows.
  • Experience working with embedded engineers.
  • Ability to work onsite in Pittsburgh five days per week.

Culture & Benefits

  • Collaborative environment with support and guidance from experienced colleagues and managers.
  • Medical, dental, and vision insurance, including HSA options.
  • Company-paid life and short- and long-term disability insurance.
  • 401(k), healthcare, dependent-care, and commuter flexible spending accounts.
  • Discretionary vacation, eight paid holidays, paid sick time, bereavement leave, and parental leave.
  • Pet insurance discounts and potential equity awards and performance-based bonuses.

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