Machine Learning Engineer, Integrity
About the Team The Integrity team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary, but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale.
What this role actually needs.
About the Team The Integrity team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary, but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. Responsibilities: - Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. - Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives. - Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches. - Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices. - Make a Difference: Monitor and maintain deployed models to ensure they continue delivering value. Your work will directly influence how AI benefits individuals, businesses, and society at large. - Master's/ PhD degree in Computer Science, Machine Learning, Data Science, or a related field. Benefits: - Master's/ PhD degree in Computer Science, Machine Learning, Data Science, or a related field. - Demonstrated experience in deep learning and transformers models - Experience with content understanding or abuse prevention with LLMs is a plus - Proficiency in frameworks like PyTorch or Tensorflow - Strong foundation in data structures, algorithms, and software engineering principles. - Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization Company context: OpenAI builds frontier AI systems, research infrastructure, and applied products for developers, enterprises, and global users.
Day-to-day expectations
OpenAI lists these responsibilities for the Machine Learning Engineer, Integrity role.
- Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact.
- Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives.
- Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches.
- Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices.
- Make a Difference: Monitor and maintain deployed models to ensure they continue delivering value. Your work will directly influence how AI benefits individuals, businesses, and society at large.
- Master's/ PhD degree in Computer Science, Machine Learning, Data Science, or a related field.
Why people would want this job
OpenAI published these compensation, benefits, or working-context details with the role.
- Master's/ PhD degree in Computer Science, Machine Learning, Data Science, or a related field.
- Demonstrated experience in deep learning and transformers models
- Experience with content understanding or abuse prevention with LLMs is a plus
- Proficiency in frameworks like PyTorch or Tensorflow
- Strong foundation in data structures, algorithms, and software engineering principles.
- Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization
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Source: jobs.ashbyhq.com · Source ID: ecf1abec-898c-4acb-a984-42858836a1ff · Confidence: 97/100 · Last checked: May 7, 2026
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