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Join OpenAI as a Machine Learning Engineer in the Monetization team, where you'll innovate and deploy advanced AI models, collaborate with top researchers, and contribute to impactful AI-driven applications.
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
- 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.
- 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.