Postdoctoral Researcher – AI Systems for ML – PhD
| Company | Meta |
|---|---|
| Location | Boston, MA, USA, Menlo Park, CA, USA |
| Salary | $117000 – $173000 |
| Type | Full-Time |
| Degrees | Bachelor’s, PhD |
| Experience Level | Senior, Expert or higher |
Requirements
- Currently has or is in the process of obtaining a PhD degree in the field of Machine Learning, Systems, Artificial Intelligence, a related field, or equivalent practical experience. Degree must be completed prior to joining Meta
- Research experience at the intersection of Systems and Machine Learning
- Experience in C, C++, Python, Lua or other related programming language
- Experience devising data-driven models and real-system experiments and design implementation for AI system optimization
- Experience with scalable machine learning systems, resource-efficient AI data and algorithm scaling, or neural network architectures
- Experience with memory and energy-efficient AI systems, environmentally-sustainable AI system designs, or AI-driven system optimization
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
- Currently has, or is in the process of obtaining a Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
Responsibilities
- Perform research to advance the science and technology of intelligent machines
- Perform research that enables learning the semantics of data (images, video, text, audio, and other modalities)
- Devise better data-driven models of AI system design and optimization
- Contribute research that leads to innovations in: Scalable machine learning systems, Resource-efficient AI data and algorithm scaling and neural network architectures, Memory and energy-efficient AI systems, Environmentally-sustainable AI system and hardware designs, AI-driven compiler, programming language, system design and optimization, System design for privacy-enhancing AI technologies
Preferred Qualifications
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, MLSys, ISCA, ASPLOS, CGO, PLDI, PACT, HPCA, MICRO
- Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open-source repositories (e.g. GitHub)
- Experience developing and optimizing systems for at-scale machine learning execution
- Experience in real-system implementations
- Experience solving analytical problems using quantitative approaches
- Experience manipulating and analyzing complex, large scale, high-dimensionality data from varying sources
- Experience in utilizing theoretical and empirical research to solve problems
- Experience building systems based on machine learning and/or deep learning methods
- Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward
- Experience working and communicating cross functionally in a team environment