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Meta is seeking a Research Engineer to join our Fundamental AI Research (FAIR) Team, a research organization focused on making significant progress in AI.
Individuals in this role are expected to be well-versed in information theory and/or generative modeling, and have a keen interest in data compression, deep learning, and computer vision.
Data compression is at the heart of all digital systems, and AI has the potential to deliver the next generation of compression codecs powered by neural networks.
Research Engineer – Neural Compression
Job Description:
- Develop highly scalable algorithms based on machine learning and neural network methodologies.
- Collaborate with FAIR scientists on novel research in compression, computer vision, information theory and generative modeling.
- Apply knowledge of relevant research domains and coding skills to platform and framework development projects.
- Adapt machine learning and neural network algorithms to best exploit modern parallel environments (e.g. distributed clusters, GPUs, TPUs, etc.).
Qualifications
- Currently has or is in the process of obtaining a PhD in the field of Computer Science, Artificial Intelligence, a related field, or equivalent practical experience. Degree must be completed prior to joining Meta.
- One or more years experience training and evaluating deep learning models and understanding of neural compression algorithms.
- 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.
- Experience developing machine learning algorithms or machine learning infrastructure in Python and PyTorch.
- Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.
Preferred:
- Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
- Industry research experience in neural compression.
- 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.
- Publication track record at conferences such as NeurIPS, ICML, ICLR, etc.
For more details to apply, Click here!
Research Engineer
Meta is seeking an early-career research engineer to join our Brain & AI team at FAIR (Fundamental AI Research) Paris, an organization focused on making research breakthroughs in AI.
Individuals in this role are expected to be knowledgeable in research areas such as ML theory, Responsible AI, reinforcement learning, computer vision, audio, and/or NLP.
Research engineers are also expected to be motivated to help produce new science that advances our understanding of intelligence.
Job Responsibilities
- Write clean and robust machine learning code
- Engineer, design, implement, and improve machine learning systems and tools for enabling research
- Collaborate effectively within their team to help advance its research goals
- Influence progress of relevant research communities by contributing to publications
Qualifications:
- 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
- Expertise in deep learning
- Experience using PyTorch or similar deep learning libraries
For more details to apply, Click here!
Research Engineer – FAIR Core Learning – USA
Meta is seeking a Research Engineer to join our Fundamental AI Research (FAIR) Team, a research organization focused on making significant progress in AI.
Advances in AI are key to our mission, spanning some of the most pressing research challenges of our generation across such areas as artificial intelligence, machine learning, computational statistics, and applied mathematics, particularly including areas such as deep learning, generative models, reinforcement learning, computer perception, natural language processing.
The ideal candidate will have a keen interest in producing new science to understand intelligence and technology to make computers more intelligent, or to work on more applied problems across the company.
Qualifications
- Currently has or is in the process of obtaining a PhD in the field of Computer Science, Artificial Intelligence, a related field, or equivalent practical experience. Degree must be completed prior to joining Meta.
- One or more years experience in reinforcement learning and/or generative modeling.
- 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.
- Experience developing machine learning algorithms or machine learning infrastructure in Python and PyTorch.
- Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.
Preferred:
- Industry research experience in reinforcement learning and/or generative modeling.
- 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.
- Publication track record at conferences such as NeurIPS, ICML, ICLR, etc.
- Software engineer experience demonstrated via an internship, work experience, coding competitions.