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Research Scientist, Machine Learning (PhD)

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Meta

Apr 23

Applications are closed

  • Job
    Full-time
    Entry Level
  • Research & Development
    Data
  • London

Requirements

  • Minimum Qualifications:
  • Currently has, or is in the process of obtaining a PhD degree or completing a postdoctoral assignment in the field of Machine Learning, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
  • Research and/or work experience in machine learning, deep learning, reinforcement learning, NLP, recommendation systems, pattern recognition, signal processing, data mining, artificial intelligence, information retrieval or computer vision.
  • Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Experience in systems software or algorithms.
  • Experience in at least one of the following: Java, C/C++, Perl, PhP, or Python Demonstrated software engineer experience via an internship, work experience, coding competitions, or used contributions in open source repositories (e.g. GitHub)
  • Preferred Qualifications:
  • 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
  • Experience with Hadoop/Hbase/Pig or Mapreduce/Swazall/Bigtable
  • Experience working with ML Frameworks such as PyTorch, Spark ML or Tensorflow
  • Experience working and communicating cross functionally in a team environment

Responsibilities

  • Develop highly scalable classifiers and tools leveraging machine learning, regression, and rules-based models with a high degree of autonomy
  • Suggest, collect and synthesize requirements and create effective feature roadmap
  • Build strong crossfunctinal 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) Actively seek and give feedback in alignment with Meta’s Performance Philosophy

FAQs

What will be my main responsibilities as a Research Scientist, Machine Learning at Meta?

As a Research Scientist, you will help build machine learning systems and models behind Meta’s products, create web applications that reach millions of people, build high volume servers and be a part of a team that’s working to help connect people around the globe.

What qualifications are required to become a Research Scientist, Machine Learning at Meta?

A PhD in a relevant field such as Computer Science, Machine Learning, or Artificial Intelligence is required for this position. Strong programming skills and experience with machine learning algorithms are also essential.

What kind of impact will I have working as a Research Scientist at Meta?

As a Research Scientist, you will have the opportunity to work on cutting-edge machine learning projects that impact millions of people around the world. Your work will help improve user experience, connect people, and drive innovation in the field of AI.

Can I expect to work on cross-functional teams as a Research Scientist at Meta?

Yes, as a Research Scientist at Meta, you will work collaboratively with other researchers, engineers, product managers, and designers to develop and implement machine learning solutions for Meta's products and services. Collaboration and teamwork are key components of the role.

Technology
Industry
10,001+
Employees
2004
Founded Year

Mission & Purpose

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.