Research Scientist, Machine Learning
1 week ago
Meta is embarking on the most transformative change to its business and technology in company history, and our Machine Learning teams are at the forefront of this evolution. By taking on crucial projects and initiatives that have never been done before, you have an opportunity to help advance the way people connect around the world.
In order to meet the demands of our scale, we approach machine learning challenges from a system engineering standpoint, pushing the boundaries of scalable computing and tying together numerous complex platforms to build models that leverage trillions of actions. Our research and production implementations leverage many of the innovations being generated from Meta’s research in Distributed Computing, Artificial Intelligence and Databases, and run on the same hardware and network specifications that are being open sourced through the Open Compute project.
As a Research Scientist at Meta, you will bring experience working on a range of recommendation, classification, and optimization problems. You will have the ability to own the whole ML life-cycle, define projects and drive excellence across teams. You will work alongside the world’s leading engineers and researchers to solve some of the most exciting and massive social data and prediction problems that exist on the web.
- Develop highly scalable classifiers and tools leveraging machine learning, regression, and rules-based models
- Suggest, collect and synthesize requirements and create effective feature roadmap Build strong cross functional partnerships and code deliverables in tandem with the engineering team
- Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)
- Perform specific responsibilities which vary by team
- Currently has, or is in the process of obtaining, a PhD degree or completing a postdoctoral assignment in the field of Computer Science, Computer Vision, Machine Learning or relevant technical field. Degree must be completed prior to joining Meta
- Programming experience in a relevant programming language
- Research and/or hands-on experience in one or more of the following areas: machine learning, NLP, recommendation systems, pattern recognition, data mining or artificial intelligence
- Relevant experience using frameworks such as PyTorch, TensorFlow or equivalent
- Proven experience to translate insights into business recommendations
- Experience with scripting languages such as Python, Javascript or Hack
- Experience building and shipping high quality work and achieving high reliability
- Demonstrated software engineer experience via an internship, work experience, coding competitions, or used contributions in open source repositories (e.g. GitHub)
- Proven track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at workshops or conferences such as ICML, NIPS, KDD or similar
- Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward
- Interpersonal experience working and communicating cross functionally in a team environment
- Exposure to architectural patterns of large scale software applications
- PhD degree or research focused Master degree in ML areas
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Tell employers what skills you have
TensorFlow
Machine Learning
MASSIVE
Architectural Patterns
Physics
Artificial Intelligence
Computer Vision
Data Mining
PyTorch
Grants
Python
Prediction
Publications
Pattern Recognition
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