Software Engineer, Machine Learning
Menlo Park, CA | Remote, US
- 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, 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. - 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-theart 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 (such as distributed clusters, multicore SMP, and GPU). - Telecommute from anywhere in the US permitted.
- Requires a Master’s degree in Computer Science, Computer Software, Computer Engineering, Applied Sciences, Mathematics, Physics, or related field. Requires completion of a university-level course, research project, internship, or thesis in the following:
- 1. Machine Learning Framework(s): PyTorch, MXNet, or Tensorflow
- 2. Machine learning, recommendation systems, computer vision, natural language processing, data mining, or distributed systems
- 3. Translating insights into business recommendations
- 4. Hadoop, HBase, Pig, MapReduce, Sawzall, Bigtable, or Spark
- 5. Developing and debugging in C, C++, and Java
- 6. Scripting languages: 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 as evidenced by file manipulation, advanced commands, and shell scripting
- 12. Build highly-scalable performant solutions
- 13. Data processing, programming languages, databases, networking, operating systems, computer graphics, or human-computer interaction
- 14. Applying algorithms and core computer science concepts to real world systems as evidenced by recognizing and matching patterns from different areas of computer science in
production systems - 15. Distributed systems.
Individual pay is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base salary, Meta offers benefits. Learn more about benefits at Meta.
Tags: Bigtable Classification Computer Science Computer Vision Data Mining Deep Learning Distributed Systems Engineering Git GPU Hadoop Haskell HBase Java Linux Machine Learning Mathematics MXNet NLP Perl PHP Physics Python PyTorch RDBMS Research Shell scripting Spark SQL TensorFlow VR
Perks/benefits: Career development Equity Health care Salary bonus
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