Research Engineer - Core ML - FB Search Team
Job Description
Meta is seeking a Research ML engineer to join our Facebook Search team. We are part of a multi-year investment in a modern search experience across Instagram & Facebook that is complementary to our recommendation strategy. We are building search systems on a foundation of state-of-the-art AI technology, and re-engineering core components of Search like query and document understanding; query suggestions / autocomplete; building, fine tuning and distilling Large Language Models; and reinforcement learning for language model tuning.
Locations
- Menlo Park, CA, USA
Salary
58,500 - 208,000 USD / yearly
Skills Required
- Machine Learningintermediate (AI/ML)
- Deep Learningintermediate (AI/ML)
- Natural Language Processingintermediate (AI/ML)
- Pythonintermediate (Programming)
- PyTorchintermediate (Frameworks)
Required Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience (degree in Computer Science)
- Research experience in machine learning, deep learning, and/or natural language processing (experience)
- Experience with developing machine learning models at scale from inception to business impact (experience)
- Programming experience in Python and hands-on experience with frameworks such as PyTorch (experience)
- Experience with architectural patterns of large scale software applications (experience)
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment (experience)
Preferred Qualifications
- Direct experience in Search / Recommendations (experience)
- First author publications at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL) (experience)
- Master's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience (degree in Computer Science)
- A PhD in AI, computer science, data science, or related technical fields (degree in AI)
Responsibilities
- Design methods, tools, and infrastructure to push forward the state of the art in search and recommendation models
- Define research goals informed by long-term product roadmaps
- Contribute to experiments, including designing experimental details, developing reusable code, running evaluations, and organizing results
- Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)
- Work with a large and globally distributed team
- Contribute to publications and open-sourcing efforts
Benefits
- compensation: Bonus + equity + benefits
