Software Engineer (Machine Learning)
Burlingame, CA
- 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 diverse 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. - Demonstrates good judgment to 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 little 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).
- Master’s degree in Computer Science, Computer Software, Computer Engineering, Applied Sciences, Mathematics, Physics, or a related field. 36 months of experience in the job offered or in a computer-related occupation. Experience must include 36 months involving the following:
- 1. Python, PHP, or Haskell
- 2. Relational databases and SQL
- 3. Software development tools: Code editors (VIM or Emacs), and revision control systems (Subversion, GIT, or Perforce)
- 4. Linux, Unix, or other *nix-like OS as evidenced by file manipulation, advanced commands, and shell scripting
- 5. Build highly-scalable performant solutions
- 6. Data processing, programming languages, databases, networking, operating systems, computer graphics, or human-computer interaction
- 7. 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 - 8. Distributed Systems.
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly 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.
Tags: Classification Computer Science Deep Learning Distributed Systems Engineering Git GPU Haskell Linux Machine Learning Mathematics PHP Physics Python RDBMS Research Shell scripting SQL VR
Perks/benefits: Career development Equity / stock options Health care Salary bonus
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