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Research Scientist, Machine Learning (PhD)

AT Meta
Meta

Research Scientist, Machine Learning (PhD)

London, United Kingdom

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.

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Research Scientist, Machine Learning (PhD) Responsibilities:
  • 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
Minimum Qualifications:
  • 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.
  • Experience programming 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
  • Experience in systems software or algorithms
  • Must obtain work authorization in 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.
Preferred Qualifications:
  • 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
About Meta:

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.

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

Client-provided location(s): London, UK
Job ID: a1KDp00000E2KANMA3
Employment Type: Other

Perks and Benefits

  • Health and Wellness

    • Health Insurance
    • Health Reimbursement Account
    • Dental Insurance
    • Vision Insurance
    • Life Insurance
    • Short-Term Disability
    • Long-Term Disability
    • FSA
    • FSA With Employer Contribution
    • HSA
    • HSA With Employer Contribution
    • Fitness Subsidies
    • On-Site Gym
    • Mental Health Benefits
  • Parental Benefits

    • Birth Parent or Maternity Leave
    • Non-Birth Parent or Paternity Leave
    • Fertility Benefits
    • Adoption Assistance Program
    • Family Support Resources
  • Work Flexibility

    • Flexible Work Hours
    • Remote Work Opportunities
    • Hybrid Work Opportunities
  • Office Life and Perks

    • Commuter Benefits Program
    • Casual Dress
    • Happy Hours
    • Snacks
    • Some Meals Provided
    • Company Outings
    • On-Site Cafeteria
    • Holiday Events
  • Vacation and Time Off

    • Paid Vacation
    • Unlimited Paid Time Off
    • Paid Holidays
    • Personal/Sick Days
    • Sabbatical
    • Leave of Absence
  • Financial and Retirement

    • 401(K)
    • 401(K) With Company Matching
    • Pension
    • Company Equity
    • Performance Bonus
    • Relocation Assistance
    • Financial Counseling
  • Professional Development

    • Learning and Development Stipend
    • Promote From Within
    • Mentor Program
    • Shadowing Opportunities
    • Access to Online Courses
    • Lunch and Learns
    • Internship Program
  • Diversity and Inclusion

    • Diversity, Equity, and Inclusion Program
    • Employee Resource Groups (ERG)
    • Founder led

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