OpenAI

Data Engineer, Hardware & Consumer Devices

OpenAI • $135K — $160K *
Consumer Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in Data Engineering or related field
  • Strong understanding of data architecture and distributed systems
  • Proven ability to design and operate complex data systems
  • Experience with production-grade data pipelines across diverse data sources
  • Ability to make informed technical decisions in evolving environments

Responsibilities

  • Design and implement scalable data pipelines and platforms
  • Integrate complex data from manufacturing and operational systems
  • Develop reusable datasets and data architectures for multiple teams
  • Connect manufacturing conditions with product performance metrics
  • Prepare data systems for scaling from development to consumer deployment
  • Collaborate with cross-functional teams to translate requirements into solutions
  • Establish engineering standards and data quality practices

Benefits

  • Opportunity to shape the technical direction of the organization
  • Significant ownership over technical decisions
  • Collaborative work environment with cross-functional teams
  • Focus on building foundational systems rather than just optimizing existing ones
  • Exposure to cutting-edge hardware and consumer technology
Full Job Description
About the role:

As a Data Engineer, you'll design, build, and scale the data infrastructure that powers OpenAI's hardware and consumer devices organization.

You'll tackle technically challenging problems involving complex data sources, evolving operational requirements, and systems that need to scale from early development through manufacturing and consumer deployment.

Unlike roles focused primarily on supporting individual analytics projects, this position emphasizes building durable, reusable data foundations that enable multiple teams and use cases.

You'll have significant ownership over technical decisions, work closely with partners across engineering, manufacturing, operations, and Data Science, and help define how we approach Data Engineering as the organization grows.

In this role, you will:
  • Build foundational data infrastructure: Design and implement reliable, scalable data pipelines, platforms, and datasets that support hardware development, manufacturing, customer operations, and device performance.
  • Connect complex data ecosystems: Integrate information across manufacturing systems, factory operations, device telemetry, quality assurance, and customer-facing operational systems.
  • Establish durable data models: Develop reusable datasets and data architectures that enable consistent measurement, investigation, and decision-making across multiple teams.
  • Enable manufacturing and quality intelligence: Connect manufacturing conditions and production history with downstream product performance, reliability, returns, and failure signals.
  • Prepare for scale: Design systems that evolve from early-stage development and initial production to increasingly complex operations and large-scale consumer deployment.
  • Partner across disciplines: Work with hardware and software engineers, manufacturing teams, operations leaders, and Data Scientists to translate emerging requirements into robust technical solutions.
  • Shape our technical direction: Help establish engineering standards, architectural principles, data quality practices, and infrastructure decisions that will influence the organization for years to come.

You might thrive in this role if you:
  • Are comfortable making architectural decisions as requirements evolve and the right solutions aren't immediately obvious.
  • Are highly self-directed and can take broad, ambiguous problems from exploration through implementation.
  • Enjoy working directly with cross-functional partners and understanding how technical decisions affect real products and operational outcomes.
  • Have a builder's mentality and are energized by creating foundational systems rather than exclusively optimizing mature infrastructure.
  • Hold a high bar for engineering quality while remaining pragmatic about the speed and flexibility required in an early-stage environment.

Minimum Qualifications:
  • Have exceptional Data Engineering fundamentals and a track record of designing, building, and operating complex data systems.
  • Bring strong technical judgment around data architecture, distributed systems, data modeling, reliability, and scalability.
  • Have experience developing production-grade pipelines and infrastructure across heterogeneous data sources.

Bonus points if you have:
  • Experience with hardware, consumer electronics, connected devices, or IoT.
  • Experience building data infrastructure for manufacturing, factory operations, or supply-chain systems.
  • Familiarity with device telemetry, reliability engineering, product quality, or failure analysis.
  • Experience supporting customer operations, technical support, or Trust & Safety.
  • A track record of building data platforms or foundational infrastructure in a startup or rapidly scaling organization.


Prior hardware experience is not required. We value exceptional engineering ability, intellectual curiosity, and the capacity to learn new domains quickly.

About OpenAI

OpenAI is an artificial intelligence research laboratory consisting of the for-profit corporation OpenAI LP and its parent company, the non-profit OpenAI Inc. The company was founded in 2015 by a group of technology leaders, including Elon Musk, Sam Altman, Greg Brockman, Ilya Sutskever, and John Schulman. OpenAI's mission is to develop and promote friendly AI for the betterment of humanity. The company has developed a number of cutting-edge AI technologies, including GPT-3, a language processing system that can generate human-like text. OpenAI has received funding from a number of high-profile investors, including LinkedIn co-founder Reid Hoffman and venture capitalist Peter Thiel.
Learn more about OpenAI
Size
100 employees
Industry
Founded
2015

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