Machine Learning Engineer, Monetization AI/ML
Remote • San Francisco • FullTime
Posted 6h ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
Machine Learning Engineer
About the job
As a Research Engineer in OpenAI's Monetization 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. If you're excited about making AI technology accessible and impactful, this role is your chance to make a significant mark. This role operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment, partnering closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale.
Responsibilities
- Design and deploy advanced machine learning models to solve real-world problems.
- Bring OpenAI's research from concept to implementation, creating AI-driven applications.
- Collaborate with researchers, software engineers, and product managers to deliver AI-powered solutions.
- Implement scalable data pipelines and optimize models for performance and accuracy.
- Ensure deployed models are production-ready and contribute to projects requiring cutting-edge technology.
- Engage with the latest developments in machine learning and AI, participate in code reviews, and share knowledge.
- Monitor and maintain deployed models to ensure they continue delivering value.
Requirements
- 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.
- Familiarity with methods of training and fine-tuning large language models (e.g., distillation, supervised fine-tuning, policy optimization).
- Excellent problem-solving and analytical skills with a proactive approach.
- Ability to work collaboratively with cross-functional teams.
- Ability to move fast in an environment with loosely defined tasks and competing priorities.
- Willingness to own problems end-to-end and acquire necessary knowledge.