Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI
Data Engineering @ 8
Data Modeling @ 6
Data Pipelines
Data Science @ 3
Distributed Systems @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
OpenAI is building a new generation of AI-powered consumer devices. The Data Engineering team establishes the foundational data infrastructure supporting product development, manufacturing, launch, and ongoing operations. The team builds systems connecting information across the device lifecycle so engineering, operations, and Data Science teams can understand product performance, identify problems, and make better decisions.
This is an early-stage organization with significant greenfield opportunities. The role involves shaping technical foundations for a rapidly growing business and building systems that scale alongside its products.
Responsibilities
- Design and implement reliable, scalable data pipelines, platforms, and datasets supporting hardware development, manufacturing, customer operations, and device performance.
- Integrate information across manufacturing systems, factory operations, device telemetry, quality assurance, and customer-facing operational systems.
- Develop reusable datasets and data architectures that enable consistent measurement, investigation, and decision-making across teams.
- Connect manufacturing conditions and production history with downstream product performance, reliability, returns, and failure signals.
- Design systems that evolve from early-stage development and initial production to increasingly complex operations and large-scale consumer deployment.
- Partner with hardware and software engineers, manufacturing teams, operations leaders, and Data Scientists to translate requirements into robust technical solutions.
- Establish engineering standards, architectural principles, data quality practices, and infrastructure decisions.
- Take ownership of technical decisions and work through complex data sources and evolving operational requirements.
Requirements
- Exceptional Data Engineering fundamentals and a track record of designing, building, and operating complex data systems.
- Strong technical judgment in data architecture, distributed systems, data modeling, reliability, and scalability.
- Experience developing production-grade pipelines and infrastructure across heterogeneous data sources.
- Ability to make architectural decisions as requirements evolve and solutions are not immediately obvious.
- Ability to work independently on broad, ambiguous problems from exploration through implementation.
- Strong cross-functional collaboration skills and an understanding of how technical decisions affect products and operational outcomes.
- High standards for engineering quality combined with pragmatism in an early-stage environment.
Bonus Qualifications
- 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.
- Experience building data platforms or foundational infrastructure in a startup or rapidly scaling organization.
Prior hardware experience is not required. OpenAI values exceptional engineering ability, intellectual curiosity, and the capacity to learn new domains quickly.
Benefits
- Base salary range of $295,000–$445,000 per year.
- Equity and performance-related bonuses for eligible employees.
- Medical, dental, and vision insurance, with employer contributions to Health Savings Accounts.
- Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses.
- 401(k) retirement plan with employer match.
- Paid parental leave, medical leave, and caregiver leave.
- Paid time off, company holidays, office closures, and paid sick or safe time.
- Mental health and wellness support.
- Employer-paid basic life and disability coverage.
- Annual learning and development stipend.
- Daily office meals and eligible meal delivery credits.
- Relocation support for eligible employees.
- Additional benefits may include charitable donation matching and wellness stipends.
OpenAI is an equal opportunity employer and provides reasonable accommodations to applicants with disabilities. Background checks are administered in accordance with applicable law.