Senior+ Software Engineer - Research Platform, Consumer Devices
Used Tools & Technologies
Machine Learning GenAIRequired Skills & Competences
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.
Debugging @ 4
API @ 4
GPU @ 4
Observability @ 4
Generative AI @ 4
AI @ 4
Reinforcement Learning @ 4
- 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
The Future of Computing Research team is an Applied Research team within the Consumer Devices group focused on developing new methods and models as we advance forward in our mission of building AGI that benefits all of humanity.
As a Software Engineer on the Future of Computing Research team, you will work with ML researchers and design talent to push the frontier of model capabilities. You will build tools and services that enable AI research, evaluation, and data generation workflows, ensuring research artifacts have a clear lifecycle, runs are reproducible and observable, and results provide useful evidence for product and model-training decisions.
This role is based in San Francisco, CA. The team uses a hybrid work model (four days in the office per week) and offers relocation assistance to new employees.
Responsibilities
- Build web applications, APIs, data models, and backend services for AI research workflows.
- Build tools to author and manage evaluation tasks, rubrics, graders, suites, and rollout configurations, including workflows for publishing, versioning, auditing, and sharing research artifacts.
- Automate evaluation runs and generate useful reports for design, research, and engineering teams.
- Support synthetic data generation workflows for multimodal and conversational research, including tools that combine transcripts, media, and model comparisons.
- Translate product and research questions into measurable scenarios, automated graders, and human-evaluation campaigns; develop measures of task quality, coverage, diversity, and semantic spread.
- Diagnose issues across application code, workers, model endpoints, deployments, and compute infrastructure; improve reliability through health checks, observability, reproducible launch paths, data integrity safeguards, and automated verification.
- Lead migrations and dependent changes across research tools, evaluation systems, and supporting services.
- Partner closely with designers, model researchers, research engineers, and infrastructure teams; onboard contributors to create high-quality evaluation and synthetic-data workflows.
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 technical and non-technical users.
- Comfortable debugging distributed workflows and production infrastructure.
- Strong product judgment and ability to translate ambiguous requirements into concrete plans.
- Effective communicator and collaborator across engineering, design, and research.
Nice to have
- Expertise in synthetic data generation, simulation, conversational AI, speech, video, motion, or embodied interaction.
- Experience with automated graders, human evaluation, supervised fine-tuning, reinforcement learning, or experiment- and dataset-management platforms.
- Experience operating GPU-backed inference or rollout workloads at very large scale.
Benefits
- 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 and paid medical and caregiver leave.
- Paid time off and 13+ paid company holidays, plus paid sick or safe time as required by law.
- Mental health and wellness support; employer-paid basic life and disability coverage.
- Annual learning and development stipend.
- Daily meals in offices and meal delivery credits as eligible.
- Relocation support for eligible employees.
- Additional taxable fringe benefits (charitable donation matching, wellness stipends, etc.).
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. The company emphasizes safety, diverse perspectives, and equal opportunity employment. Background checks are administered in accordance with applicable law. Reasonable accommodations for applicants with disabilities are available via the provided links in the posting.