Meta - Salem, OR

posted 2 months ago

Full-time - Mid Level
Remote - Salem, OR
5,001-10,000 employees
Web Search Portals, Libraries, Archives, and Other Information Services

About the position

Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., is seeking a Software Engineer specializing in Machine Learning to join our innovative team. In this role, you will be responsible for researching, designing, developing, and testing operating systems-level software, compilers, and network distribution software that addresses massive social data and prediction challenges. You will work on a variety of problems including ranking, classification, recommendation, and optimization, which are critical to enhancing user experience and business outcomes. Your contributions will directly impact areas such as payment fraud detection, click-through or conversion rate prediction, and collaborative filtering. As a Software Engineer, you will develop highly scalable systems and algorithms that leverage deep learning, data regression, and rules-based models. You will be expected to analyze and synthesize requirements, identify bottlenecks in technology, systems, and tools, and propose solutions that significantly improve efficiency. You will collaborate closely with the engineering team, receiving general instructions from your supervisor while delivering code that meets project specifications. This position allows for telecommuting from anywhere in the US, providing flexibility in your work environment. The ideal candidate will have a strong background in machine learning frameworks and experience in adapting standard methods to exploit modern parallel environments, such as distributed clusters and GPUs. You will be part of a team that is at the forefront of building the next evolution in social technology, moving beyond traditional 2D screens to immersive experiences in augmented and virtual reality.

Responsibilities

  • Research, design, develop, and test operating systems-level software, compilers, and network distribution software for massive social data and prediction problems.
  • Work on a range of ranking, classification, recommendation, and optimization problems, including payment fraud detection and click-through rate prediction.
  • Develop highly scalable systems, algorithms, and tools leveraging deep learning and data regression.
  • Analyze and synthesize requirements and identify bottlenecks in technology, systems, and tools.
  • Develop solutions that significantly improve efficiency and leverage large datasets using state-of-the-art deep learning techniques.
  • Collaborate with the engineering team to deliver code based on general instructions from the supervisor.
  • Adapt standard machine learning methods for modern parallel environments, such as distributed clusters and GPUs.

Requirements

  • Master's degree in Computer Science, Computer Software, Computer Engineering, Applied Sciences, Mathematics, Physics, or related field.
  • Three years of work experience in machine learning frameworks such as PyTorch, MXNet, or TensorFlow.
  • Experience in machine learning, recommendation systems, computer vision, natural language processing, data mining, or distributed systems.
  • Proven ability to translate insights into business recommendations.
  • Experience with Hadoop, HBase, Pig, MapReduce, Sawzall, Bigtable, or Spark.
  • Proficiency in scripting languages such as Perl, Python, PHP, or shell scripts.
  • Experience with relational databases and SQL.
  • Familiarity with Linux, UNIX, or other *nix-like operating systems.
  • Ability to build highly-scalable performant solutions and apply algorithms to real-world systems.

Nice-to-haves

  • Experience with human-computer interaction.
  • Knowledge of advanced commands and shell scripting in *nix-like OS.

Benefits

  • Competitive salary ranging from $229,965 to $240,240 per year plus bonus and equity.
  • Comprehensive health benefits including medical, dental, and vision insurance.
  • Flexible work arrangements including telecommuting options.
  • Opportunities for professional development and continued education.
  • Equity in the company as part of the compensation package.
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