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5 часов назад

Data Engineer, ML Ops

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
Data Engineer, ML Ops (Python/SQL/Robotics): Architecting scalable data platforms and reliable pipelines for machine learning, robotics, experimentation, and production AI with an accent on multi-modal sensor data, data quality, and governance. Focus on modeling high-volume real-world datasets, improving pipeline observability and orchestration, and enabling teams to deploy reliable AI systems.

Location: Columbus, Ohio, United States. The role may involve access to export-controlled information and compliance with U.S. export-control regulations, including ITAR and EAR; candidates may need to meet the definition of a U.S. Person where required.

Company

hirify.global develops AI-driven robotic systems that combine perception, reasoning, and control to operate reliably in real-world industrial environments.

What you will do

  • Partner with software, machine learning, robotics, and analytics teams to translate data needs into well-modeled tables and data products.
  • Develop and extend data models and production pipelines for experimentation, model training and validation, reporting, and business decisions.
  • Model large-scale, multi-modal data, including sensor streams, application telemetry, system logs, and unstructured blob data.
  • Monitor pipeline health and data quality, troubleshoot failures, and improve testing and alerting.
  • Strengthen governance, lineage, documentation, and data contracts while participating in code reviews.
  • Improve the data platform’s usability, performance, and tooling through clean, tested, documented Python and SQL.

Requirements

  • At least 2 years of experience in data engineering or a closely related role supporting production data pipelines.
  • Strong proficiency in SQL and Python.
  • Hands-on experience with AWS, Snowflake, Dagster, dbt, or an equivalent modern data stack.
  • Knowledge of data modeling, data warehousing, and pipeline orchestration.
  • Ability to work directly with stakeholders, communicate clearly, take ownership, and contribute to an experienced team.
  • Ability to comply with applicable U.S. export-control regulations and confidentiality requirements; employment may require a background check.

Nice to have

  • Experience with sensor data, robotics logs, manipulation data, or other high-volume real-world datasets.

Culture & Benefits

  • Daily free lunch.
  • Flexible PTO.
  • Medical, dental, and vision coverage.
  • Six weeks of fully paid parental leave, plus an additional six to eight weeks for birthing parents.
  • 401(k) retirement plan through Empower.
  • Inclusive environment that values diverse ideas and unique thinking.

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