
Job Overview
Location
San Francisco
Job Type
Full-time
Category
Software Engineer
Date Posted
June 26, 2026
Full Job Description
đź“‹ Description
- • Build web applications, APIs, data models, and backend services to enable AI research workflows including evaluation, synthetic data generation, and artifact management.
- • Design and develop tools for authoring and managing evaluation tasks, rubrics, graders, suites, and rollout configurations with support for publishing, versioning, auditing, and sharing research artifacts.
- • Automate evaluation runs and generate actionable reports for design, research, and engineering teams to inform model training and product decisions.
- • Support synthetic data generation pipelines for multimodal and conversational AI research, integrating transcripts, media, and model comparison outputs.
- • Translate ambiguous product and research questions into measurable scenarios, automated graders, and human-evaluation campaigns, defining metrics for task quality, coverage, diversity, and semantic spread.
- • Diagnose and resolve issues across application code, worker systems, model endpoints, deployments, and compute infrastructure using health checks, observability tools, reproducible launch paths, and automated verification.
- • Lead migrations and dependent changes across research tools, evaluation systems, and supporting platform services to ensure reliability and scalability.
- • Partner closely with ML researchers, designers, research engineers, and infrastructure teams to onboard contributors and establish high-quality evaluation and synthetic-data workflows.
- • Ensure research artifacts have a clear lifecycle, runs are reproducible and observable, and results provide trustworthy evidence for decision-making while maintaining reusable, reliable systems.
- • Develop internal tools used by both technical and non-technical users to streamline research workflows without requiring bespoke engineering support for each new concept.
- • Operate and optimize systems that handle large-scale GPU-backed inference and rollout workloads in production environments.
- • Maintain data integrity safeguards and improve system reliability through automated verification and monitoring across distributed workflows.
- • Communicate clearly and collaborate effectively across engineering, design, and research disciplines to bridge qualitative judgment with rigorous quantitative evidence.
🎯 Requirements
- • 7+ years of professional software engineering experience
- • Strong full-stack experience across web applications, backend services, APIs, and data models, including ownership of complex systems spanning multiple services or repositories
- • Expertise in generative AI, multimodal models, or model-evaluation systems
- • Experience building effective internal tools for both technical and non-technical users
- • Comfort debugging distributed workflows and production infrastructure
- • Strong product judgment and ability to translate ambiguous requirements into concrete plans
🏖️ Benefits
- • Hybrid work model with four days in the office per week
- • Relocation assistance for new employees
- • Opportunity to work alongside leading ML researchers and design talent
- • Access to cutting-edge AI research and deployment systems
- • Inclusive, equal opportunity employer with commitment to diversity and reasonable accommodations
- • Compliance with San Francisco Fair Chance Ordinance and California Fair Chance Act for qualified applicants
Skills & Technologies
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About OpenAI, Inc.
OpenAI is a San Francisco-based artificial intelligence research and deployment company founded in 2015. It develops large-scale AI models such as GPT, DALL-E, and Codex, providing cloud APIs and consumer applications like ChatGPT. Originally established as a non-profit, it later created a capped-profit subsidiary to attract capital while maintaining its mission to ensure artificial general intelligence benefits all of humanity.
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