Software Engineer, Machine Learning (REMSWE15)
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, 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).
- Telecommute from anywhere in the U.S. permitted.
- Requires a Master’s degree in Computer Science, Computer Software, Computer Engineering, Applied Sciences, Mathematics, Physics, or related field and two years of work experience in the job offered or in a computer-related occupation.
- Requires two years of experience 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 compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta. Apply
Job Profile
Regions Countries Benefits/PerksBenefits Bonus Equity Long term conditions Mental health conditions Pregnancy-related support Religious beliefs
SkillsAlgorithms Bigtable C C++ Code editors Compilers Computer graphics Computer Science Computer Vision Databases Data Mining Data processing Data Regression Debugging Deep Learning Design Developing Distributed Systems Emacs Engineering Git Hadoop Haskell HBase Human-Computer Interaction Industry experience Java Linux Machine Learning MapReduce MXNet Natural Language Processing Network Distribution Network Distribution Software Networking Operating Systems Operating Systems-level Software Optimization Perforce Perl PHP Pig Programming Programming languages Python PyTorch Recommendation systems Recruiting Regression Relational databases Research Revision control systems Rules Based Models Sawzall Scripting Languages Shell scripting Shell Scripts Software Development Software Development Tools Spark SQL Subversion TensorFlow UNIX VIM Web
Tasks- Adapt machine learning methods to parallel environments
- Adapt standard machine learning methods to best exploit modern parallel environments
- Analyze and synthesize requirements and bottleneck in technology
- Code deliverables in tandem with the engineering team
- Data mining
- Develop scalable systems leveraging deep learning and data regression
- Research, design, and develop operating systems-level software
- Research, design, develop, and test operating systems-level software
- Research, design, develop, and test operating systems-level software, compilers, and network distribution software for massive social data and prediction problems
- Work on ranking, classification, recommendation, and optimization problems
2 years
EducationApplied Sciences Business Computer Engineering Computer Graphics Computer Science Computer Software Design Engineering Master Master’s Degree in Computer Science Mathematics Physics Related Field Technology
RestrictionsTelecommute from anywhere in the U.S. permitted
TimezonesAmerica/Anchorage America/Chicago America/Denver America/Los_Angeles America/New_York Pacific/Honolulu UTC-10 UTC-5 UTC-6 UTC-7 UTC-8 UTC-9