About the job
As a Research Engineer in OpenAI's Applied Voice Team, you will have the opportunity to work with some of the brightest minds in AI. You'll design and build state-of-the-art speech models (speech-to-speech, transcribing, text to speech, etc.) and help turn research breakthroughs into tangible into tangible OpenAI speech products. If you're excited about making AI technology accessible and impactful, this role is your chance to make a significant mark.
Responsibilities
Innovate and Build: Design and build 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 software engineers, product managers and forward deployed engineers to understand complex business challenges, address customer concerns 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
Minimum
Master's/ PhD degree in Computer Science, Machine Learning, or a related field.
2+ years of professional engineering experience (excluding internships) in relevant roles at tech and product-driven companies.
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.
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
Preferred
Experience with speech models is a plus.
Familiarity with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization