Software Engineer, Machine Learning

About the Role

Key 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.
• Work 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.
• Receive 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).
• Research, design and develop new algorithms to improve the efficiency of Meta's platforms, gathering data for machine learning training and running experiments.
• Identify potential improvements for Meta's products and monitor and review current research to apply relevant ideas towards engineering projects.

Requirements

• Master's degree (or foreign degree equivalent) in Computer Science, Computer Software, Computer Engineering, Applied Sciences, or a related field.
• Completion of a university-level course/research project/internship/thesis in machine learning frameworks such as PyTorch, MXNet, or TensorFlow.
• Experience with machine learning, recommendation systems, computer vision, natural language processing, data mining, or distributed systems.
• Ability to translate insights into business recommendations.
• Knowledge of Hadoop, HBase, Pig, MapReduce, Sawzall, Bigtable, or Spark.
• Proficiency in developing and debugging in C, C++, and Java.
• Familiarity with scripting languages such as Perl, Python, PHP, or shell scripts.
• Experience with relational databases and SQL.
• Knowledge of software development tools like code editors (VIM or Emacs) and revision control systems (Subversion, GIT, or Perforce).
• Experience with Linux, UNIX, or other *nix-like operating systems, including file manipulation, advanced commands, and shell scripting.
• Ability to build highly-scalable, performant solutions.
• Understanding of data processing, programming languages, databases, networking, operating systems, computer graphics, or human-computer interaction.
• Applying algorithms and core computer science concepts to real-world systems and recognizing patterns across different areas of computer science in production environments.
• Experience with distributed systems.

Qualifications

• Master's degree or equivalent in a related field.
• Experience with machine learning frameworks and large-scale data systems.