Engineering Manager, MLE
San Francisco • FullTime
Posted 2mo ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
On-site
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
As a Machine Learning Engineer in OpenAI's Integrity team, you will work with state-of-the-art models and classifiers, experiment with new architectures, and advance our capabilities in content and user understanding. This role offers the chance to transform research breakthroughs into tangible solutions that enhance platform trust and safety, particularly for those excited about training LLMs and building ML models. You will be instrumental in designing and deploying advanced machine learning models to solve real-world problems, bringing AI-driven applications from concept to implementation. Collaboration with researchers, software engineers, and product managers is key to delivering AI-powered solutions for complex business challenges. You will also optimize and scale data pipelines, ensure models are production-ready, and contribute to projects requiring cutting-edge technology. Staying ahead of the curve in machine learning and AI developments, participating in code reviews, and leading by example are essential aspects of this role, as is monitoring and maintaining deployed models to ensure continued value delivery.
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 machine learning models are production-ready.
- Stay updated on the latest developments in machine learning and AI.
- Participate in code reviews and share knowledge.
- Lead by example to maintain high-quality engineering practices.
- Monitor and maintain deployed models to ensure they continue delivering value.
Requirements
- Master's or PhD degree in Computer Science, Machine Learning, Data Science, or a related field.
- Demonstrated experience in deep learning and transformer 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.
- 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.
- Proactive approach to challenges.
- 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.