Meta - Lincoln, NE

posted 2 months ago

Full-time - Mid Level
Remote - Lincoln, NE
Web Search Portals, Libraries, Archives, and Other Information Services

About the position

Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., is at the forefront of building technologies that facilitate connections, foster communities, and enhance business growth. Since its inception in 2004, Facebook has revolutionized the way individuals interact. With the introduction of applications and services such as Messenger, Instagram, and WhatsApp, Meta has empowered billions globally. Currently, Meta is advancing beyond traditional 2D screens, venturing into immersive experiences like augmented and virtual reality, aiming to shape the next evolution in social technology. The Software Engineer, Machine Learning position involves a multifaceted role where the individual will research, design, develop, and test operating systems-level software, compilers, and network distribution software tailored for massive social data and prediction challenges. The role requires industry experience in tackling a variety of ranking, classification, recommendation, and optimization problems, including but not limited to payment fraud detection, click-through or conversion rate prediction, and spam detection. The successful candidate will work on moderately complex problems, developing highly scalable systems, algorithms, and tools that leverage deep learning, data regression, and rule-based models. In this role, the engineer will be expected to suggest, collect, analyze, and synthesize requirements while identifying bottlenecks in technology, systems, and tools. The position also involves developing solutions that significantly enhance efficiency and exploring state-of-the-art deep learning techniques. The engineer will receive general instructions from a supervisor and will collaborate closely with the engineering team to deliver code. Additionally, the role allows for telecommuting from anywhere in the US, providing flexibility in the work environment.

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 such as payment fraud detection and click-through rate prediction.
  • Develop highly scalable systems, algorithms, and tools leveraging deep learning, data regression, and rules-based models.
  • Analyze and synthesize requirements and identify bottlenecks in technology, systems, and tools.
  • Develop solutions that iterate orders of magnitude with higher efficiency and explore state-of-the-art deep learning techniques.
  • Collaborate with the engineering team to deliver code based on general instructions from a supervisor.
  • Adapt standard machine learning methods to exploit modern parallel environments like 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 the job offered or in a computer-related occupation.
  • Experience with 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.
  • 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 Python, PHP, or Haskell.
  • Familiarity with relational databases and SQL.
  • Experience with software development tools like VIM or Emacs, and revision control systems like Subversion, GIT, or Perforce.
  • Proficiency in Linux, UNIX, or other *nix-like operating systems.
  • Ability to build highly-scalable performant solutions.
  • Knowledge in data processing, programming languages, databases, networking, operating systems, computer graphics, or human-computer interaction.
  • Experience applying algorithms and core computer science concepts to real-world systems.

Benefits

  • Bonus
  • Equity
  • Health benefits
  • Flexible work environment
  • Telecommuting options
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