Software Engineer

Master’s degree (or foreign degree equivalent) in Computer Science, Computer Software, Computer Engineering, Applied Sciences, Mathematics, Physics, Data Science or related field
2 years of experience in the job offered or in a computer-related occupation
Experience must include 2 years of experience in the following:
1. Machine Learning Framework(s): PyTorch, MXNet, or Tensorflow
2. Machine learning, recommendation systems, ranking systems, computer vision, natural language processing, data mining, or distributed systems
3. Translating insights into business recommendations
4. Hadoop/HBase/Pig or MapReduce/Sawzall/Bigtable/Spark
5. Developing and debugging in C/C++ and Java
6. Scripting languages such as Perl, Python, PHP, or shell scripts
7. C, C++, C#, or Java
8. Python, PHP, or Haskell
9. Relational databases and SQL
10. Software development tools: Code editors (VIM or Emacs), and revision control systems (Subversion, GIT, or Perforce)
11. Linux, UNIX, or other *nix-like OS including file manipulation and simple commands
12. Building highly-scalable performant solutions
13. Distributed systems including sharding, consistency, and availability
14. Data structures and algorithms

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 classification 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.
Working 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.
Receiving 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).

No preferred qualifications provided.