Meta Postdoctoral Researcher, ML and Optimization (PhD) in Menlo Park, California
Meta is seeking a Postdoctoral Researcher to join Fundamental AI Research (FAIR), a research organization focused on making significant progress in AI. Individuals in this role are expected to be recognized experts in identified research areas such as artificial intelligence, machine learning, reinforcement learning and optimization.The ideal candidate should have a keen interest to develop novel approaches that lead to better solutions to hard optimization problems in a more efficient way, and demonstrate their usages in real-world problems, including but not limited to ML for System, AI for Design, Large Language Models, etc. Postdoc positions are one to two year fixed-term positions.
Postdoctoral Researcher, ML and Optimization (PhD) Responsibilities:
Perform fundamental and applied research to design novel machine learning guided algorithms to solve hard optimization problems. The optimization problems may (1) contain highly nonlinear and non-convex objectives, (2) contain combinatorial constraints, (3) be slow to even evaluate so that a surrogate model is needed, (4) need to be solved repeatedly, and (5) may have special structures yet to be leveraged.
Perform experiments and studies to evaluate the developed algorithms to real-world or even industry-level applications. Potential targeted applications include but are not limited to ML for System, AI for Design, Large Language Models, etc.
Discuss with the mentor(s) for research agenda, and drive them with self-motivations.
Proactively communicate with teammates and mentors about progress, potential issues and requests in order to achieve the goal.
Actively collaborative attitude.
Draft publications and revise them based on the feedback from colleagues, mentor(s) and reviewers.
Currently has or is in the process of obtaining a PhD degree in the field of Artificial Intelligence, Machine Learning, Operation Research or a related field, or equivalent practical experience. Degree must be completed prior to joining Meta
Experience in learning frameworks (such as PyTorch, TensorFlow), C, C++, Python
Have basic research background with publications in conferences/journals in the related fields
Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops, journals or conferences in Machine Learning (NeurIPS, ICML, ICLR). Other closely related track records (e.g., Operation Research, MLSys) will also be considered in a case-by-case manner
Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
Experience with manipulating and analyzing complex, large scale, high-dimensionality data from varying sources
Experience building systems based on machine learning and/or deep learning methods
Experience solving complex problems and comparing alternative solutions, trade-offs, and diverse points of view to determine a path forward
Experience working and communicating cross functionally in a team environment
$116,000/year to $160,000/year + benefits
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