Machine Learning Engineer, Integrity
Description
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.
The Integrity team is at the front lines of defending against financial abuse, scaled attacks, and other forms of misuse that could undermine the user experience or harm our operational stability.
About the Role
As a Machine Learning Engineer in OpenAI's Applied Group, you will have the opportunity to work with some of the brightest minds in AI. You'll contribute to deploying state-of-the-art models in production environments, helping turn research breakthroughs into tangible solutions that improve the trust and safety of our platform. If you're excited about fine tuning LLMs and building ML models this role is your chance to make a significant mark.
In this role, you will:
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.
Qualifications
Master's/ PhD degree in Computer Science, Machine Learning, Data Science, or a related field.
Demonstrated experience in deep learning and transformers models
Proficiency in frameworks like PyTorch or Tensorflow
Strong foundation in data structures, algorithms, and software engineering principles.
Experience with search relevance, ads ranking or LLMs is a plus.
Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization
Excellent problem-solving and analytical skills, with a proactive approach to challenges.
Ability to work collaboratively with cross-functional teams.
Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines
Enjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done