About this role
Full Time Mid-level Software Engineer, Machine Learning in machine learning at Meta in Menlo Park, CA. Apply directly through the link below.
At a glance
- Work mode
- Office
- Employment
- Full Time
- Location
- Menlo Park, CA
- Experience
- Mid-level · 2+ years
Core stack
- Natural Language Processing
- Computer Engineering
- Machine Learning
- Computer Science
- Computer Vision
- Deep Learning
- Data Science
- Optimization
- Distributed
- Efficiency
- Haskell
- Payment
- Python
- Hadoop
- Design
- Spark
- Linux
- Shell
- Perl
- Unix
- PHP
- SQL
- Git
Quick answers
What are the qualifications?
Master’s degree (or foreign degree equivalent) in Computer Science, Computer Software, Computer Engineering, Applied Sciences, Mathematics, Physics, Data Science or a related field and 2 years of work experience in the job offered or in a computer-related occupation
What skills are required?
Natural Language Processing, Computer Engineering, Machine Learning, Computer Science, Computer Vision, Deep Learning, Data Science, Optimization, Distributed, Efficiency, and more.
Meta is hiring for this role. Visit career page
Menlo Park, United States
Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps and services like Messenger, Instagram, and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. To apply, click “Apply to Job” online on this web page.
Responsibilities
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).
Qualifications
Master’s degree (or foreign degree equivalent) in Computer Science, Computer Software, Computer Engineering, Applied Sciences, Mathematics, Physics, Data Science or a related field and 2 years of work experience in the job offered or in a computer-related occupation
* Experience must include 2 years in the following:
* Machine learning, recommendation systems, computer vision, natural language processing, data mining, or distributed systems
* Translating insights into business recommendations
* Hadoop/HBase/Pig or MapReduce/Sawzall/Bigtable/Spark
* Scripting languages such as Perl, Python, PHP, or shell scripts
* Python, PHP, or Haskell
* Relational databases and SQL
* Software development tools: Code editors (VIM or Emacs), and revision control systems (Subversion, GIT, or Perforce)
* Linux, UNIX, or other *nix-like OS as evidenced by file manipulation, advanced commands, and shell scripting
* Build highly-scalable performant solutions
* Data processing, programming languages, databases, networking, operating systems, computer graphics, or human-computer interaction
* 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
* Distributed systems
Responsibilities
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).
Qualifications
Master’s degree (or foreign degree equivalent) in Computer Science, Computer Software, Computer Engineering, Applied Sciences, Mathematics, Physics, Data Science or a related field and 2 years of work experience in the job offered or in a computer-related occupation
* Experience must include 2 years in the following:
* Machine learning, recommendation systems, computer vision, natural language processing, data mining, or distributed systems
* Translating insights into business recommendations
* Hadoop/HBase/Pig or MapReduce/Sawzall/Bigtable/Spark
* Scripting languages such as Perl, Python, PHP, or shell scripts
* Python, PHP, or Haskell
* Relational databases and SQL
* Software development tools: Code editors (VIM or Emacs), and revision control systems (Subversion, GIT, or Perforce)
* Linux, UNIX, or other *nix-like OS as evidenced by file manipulation, advanced commands, and shell scripting
* Build highly-scalable performant solutions
* Data processing, programming languages, databases, networking, operating systems, computer graphics, or human-computer interaction
* 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
* Distributed systems