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Software Engineer (Machine Learning)

M

Location
United States
Base Salary
171k-200k USD
Meta

Job Description

Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps and services 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. To apply, click “Apply to Job” online on this web page.Software Engineer (Machine Learning) Responsibilities
  • Research, design, develop, and test operating systems-level software, compilers, and network distribution software for massive social data and prediction problems.
  • Have industry experience working on a range of ranking, classification, recommendation, and optimization problems, e.g.
  • payment fraud, click-through or conversion rate prediction, click-fraud detection, ads/feed/search ranking, text/sentiment classification, collaborative filtering/recommendation, or spam detection.
  • Working on problems of moderate scope, develop highly scalable systems, algorithms and tools leveraging deep learning, data regression, and rules based models.
  • Suggest, collect, analyze and synthesize requirements and bottleneck in technology, systems, and tools.
  • Develop solutions that iterate orders of magnitude with a higher efficiency, efficiently leverage orders of magnitude and more data, and explore state-of-the-art deep learning techniques.
  • Receiving general instruction from supervisor, 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).
  • Telecommuting is permitted from anywhere in the U.S.
Minimum Qualifications
  • Requires a Master's degree (or foreign equivalent) in Computer Science, Engineering, Applied Sciences, Mathematics, Physics, or related field.
    Requires 12 months of experience involving the following skills:
  • 1. Machine Learning Framework(s): PyTorch, MXNet, or Tensorflow
    2. Machine learning, recommendation systems, computer vision, natural language processing, data mining, or distributed systems
  • 3. Translating insights into business recommendations
  • 4. Hadoop/HBase/Pig or MapReduce/Sawzall/Bigtable/Spark
  • 5. Developing and debugging in C/C++ and Java
  • 6. Scripting languages such as Perl, Python, PHP, or shell scripts
  • 7. C, C++, C#, or Java
  • 8. Python, PHP, or Haskell
  • 9. Relational databases and SQL
  • 10. Software development tools: Code editors (VIM or Emacs), and revision control systems (Subversion, GIT, or Perforce)
  • 11. Linux, UNIX, or other *nix-like OS as evidenced by file manipulation, advanced commands, and shell scripting
  • 12. Build highly-scalable performant solutions
  • 13. Data processing, programming languages, databases, networking, operating systems, computer graphics, or human-computer interaction
  • 14. Applying algorithms and core computer science concepts to real world systems as evidenced by recognizing and matching patterns from different areas of computer science in production systems
  • 15. Distributed systems.
LocationsAbout 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. Meta is committed to providing reasonable support (called accommodations) in our recruiting processes for candidates with disabilities, long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support. If you need support, please reach out to [email protected]. $१,७१,३०३/year to $२,००,२००/year + bonus + equity + benefits

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

Advice from our career coach

A successful applicant for the Software Engineer (Machine Learning) position at Meta Platforms, Inc. should possess a Master's degree in Computer Science or related fields, along with 12 months of relevant experience. Key qualifications include familiarity with machine learning frameworks such as PyTorch, MXNet, or TensorFlow, as well as experience in areas like recommendation systems, computer vision, and natural language processing. To stand out as an applicant, candidates should also demonstrate proficiency in programming languages like C/C++ and Java, as well as scripting languages such as Perl, Python, or PHP. Additionally, experience with relational databases, SQL, and distributed systems will be beneficial. Here are some specific tips and insights for candidates:

  • Highlight any experience working on ranking, classification, recommendation, and optimization problems in your resume.
  • Emphasize your expertise in machine learning frameworks and your ability to translate insights into actionable business recommendations.
  • Showcase your proficiency in programming languages like C/C++, Java, and scripting languages like Perl, Python, or PHP.
  • Demonstrate your knowledge and experience with relational databases, SQL, and distributed systems.
  • Describe any projects where you have developed scalable systems leveraging deep learning, data regression, and rules-based models.

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