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.
• Work on a range of ranking, classification, recommendation, and optimization problems such as payment fraud, click-through or conversion rate prediction, click-fraud detection, ads/feed/search ranking, text/sentiment classification, collaborative filtering/recommendation, or spam detection.
• 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 improve efficiency by orders of magnitude and explore state-of-the-art deep learning techniques.
• Code deliverables in tandem with the engineering team, receiving general instruction from supervisor.
• Adapt standard machine learning methods to exploit modern parallel environments such as distributed clusters, multicore SMP, and GPU.

Requirements

• Bachelor's degree (or foreign degree equivalent) in Computer Science, Computer Software, Computer Engineering, Applied Sciences, Mathematics, Physics, or related field.
• Two years of work experience in the job offered or in a computer-related occupation.
• Experience with Machine Learning Frameworks: 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.
• Experience with Hadoop, HBase, Pig, MapReduce, Sawzall, Bigtable, or Spark.
• Proficiency in developing and debugging in C, C++, and Java.
• Knowledge of scripting languages: Perl, Python, PHP, or shell scripts.
• Experience with C, C++, C#, or Java, and Python, PHP, or Haskell.
• Familiarity with relational databases and SQL.
• Experience with software development tools: code editors (VIM or Emacs), revision control systems (Subversion, GIT, or Perforce).
• Knowledge of 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 understanding of data structures and algorithms.

Qualifications

• Bachelor's degree (or foreign degree equivalent) in relevant fields.
• Two years of relevant work experience.