Research Engineer/Scientist Strategic Deployment @ OpenAI
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About The Team
The Strategic Deployment team at OpenAI makes frontier models more capable, reliable, and aligned by deploying them in high-stakes settings. They drive AI-driven transformation and create training data, evaluation methods, and techniques to shape frontier model development.
About The Role
As a Research Engineer/Scientist Strategic Deployment at OpenAI, you will tackle fundamental research questions and address AI engineering challenges rooted in real-world deployment. Your work involves building science and engineering solutions for reliable model customization, developing evaluations that fuel strategic deployments, and guiding the frontier model program.
In This Role, You Will
- Conduct research on model generalization, robustness, and steerability.
- Design evaluations to capture real-world utility and identify model gaps.
- Leverage real-world deployments to generate insights for model development.
- Collaborate with researchers, infrastructure teams, and industry experts.
You Might Thrive In This Role If You
- Have a background in ML, deep learning, or related fields.
- Possess strong engineering skills in large ML codebases.
- Are interested in foundational research informed by deployment.
- Enjoy building tools, datasets, or infrastructure for deep insights.
- Want to influence how frontier models evolve toward AGI.
About OpenAI
OpenAI is dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. The company values safety, diverse perspectives, and excellence in research and product deployment. OpenAI is an equal opportunity employer committed to fair hiring practices.
Key skills/competency
- ML
- Deep Learning
- Robustness
- Evaluation
- Deployment
- AGI
- Research
- Engineering
- Customization
- Infrastructure
How to Get Hired at OpenAI
🎯 Tips for Getting Hired
- Customize your resume: Tailor it to emphasize ML and deployment expertise.
- Highlight relevant projects: Include real-world ML research experiences.
- Show coding proficiency: Demonstrate skills in large codebases.
- Prepare for technical interviews: Practice problem-solving and research discussions.