Machine Learning Engineer

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 large scope, develop highly scalable systems, algorithms and tools leveraging deep learning, data regression, and rules based models.
• Suggest, collect, analyze and synthesize requirements and bottlenecks in technology, systems, and tools.
• Develop solutions that iterate with a higher efficiency, efficiently leverage orders of magnitude more data, and explore state-of-the-art deep learning techniques.
• Demonstrate strong engineering skills and require minimal guidance on engineering craft.
• Apply advanced machine learning methods to best exploit modern parallel environments (e.g., distributed clusters, multicore SMP, and GPU).

Requirements

• Requires a Bachelor's degree (or foreign equivalent) in Computer Science, Engineering, Applied Sciences, Mathematics, Physics or related field.
• Completion of a university-level course, research project, internship, or thesis in Machine Learning Framework(s): PyTorch, MXNet, or Tensorflow.
• Knowledge of Machine Learning Algorithms and their applications: recommendation systems, computer vision, natural language processing, or data mining.
• Experience translating insights into business recommendations.
• Familiarity with Hadoop, HBase, Pig, MapReduce, Sawzall, Bigtable, or Spark.
• Understanding of Deep Neural Networks, Probability theory, Linear Algebra, Calculus, Data Analysis.
• Knowledge of agile methodologies such as Scrum, Kanban.
• Experience developing and debugging in C, C++, and Java.
• Proficiency with scripting languages: Perl, Python, PHP, or shell scripts.
• Knowledge of Relational databases and SQL.
• Experience with software development tools: Code editors (VIM or Emacs), revision control systems (Subversion, GIT, or Perforce).
• Familiarity with Linux, UNIX, or other *nix-like OS including file manipulation and simple commands.
• Understanding of Distributed systems, including sharding, consistency, and availability.
• Experience building highly-scalable performant solutions.
• Strong knowledge of Data structures and Algorithms.

Qualifications

• Bachelor's degree or foreign equivalent in relevant fields.
• Completion of relevant coursework, research, or projects in machine learning frameworks, algorithms, and systems.

Benefits & Perks

• Annual salary ranging from $187,974 to $200,200 plus bonus, equity, and benefits.
• Meta offers additional benefits beyond base compensation.