Description
Compensation
The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws.
The total compensation package includes:
- $295K – $445K salary
- Generous equity
- Performance-related bonus(es) for eligible employees
- Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
- Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
- 401(k) retirement plan with employer match
- Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
- Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
- 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
- Mental health and wellness support
- Employer-paid basic life and disability coverage
- Annual learning and development stipend to fuel your professional growth
- Daily meals in our offices, and meal delivery credits as eligible
- Relocation support for eligible employees
- Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.
About the team
OpenAI is building a new generation of AI-powered consumer devices, creating opportunities to bring increasingly capable AI into people's everyday lives.
Our Data Engineering team is responsible for establishing the foundational data infrastructure that supports the development, manufacturing, launch, and ongoing operation of these products. We're building the systems that connect information across the entire device lifecycle, enabling engineering, operations, and Data Science partners to understand product performance, identify problems, and make better decisions.
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.
Responsibilities
- 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.
Requirements
- Exceptional Data Engineering fundamentals and a track record of designing, building, and operating complex data systems.
- Strong technical judgment around data architecture, distributed systems, data modeling, reliability, and scalability.
- Experience developing production-grade pipelines and infrastructure across heterogeneous data sources.
Nice to 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.