Machine Learning Engineer

At Abnormal Security, our mission is to create the next generation of cybersecurity technology to help organizations protect their people, assets, and peace of mind. Our platform uses machine learning and artificial intelligence to baseline communication content, user identity, and behavioral signals in real time and at scale in order to detect abnormal security patterns and invasion. Our veteran team hails from leading companies such as Google, Twitter, Pinterest, Amazon, Microsoft, and Expanse. We are located in San Francisco and New York City. 

We are tackling hard and unsolved cybersecurity problems, and machine learning is the only way we will succeed. As a member of the machine learning team, you will be responsible for developing and improving ML models to detect attacks, and coming up with new and clever ways to pull signals out of huge amounts of data. Your work will be open ended, but goal directed. 

Requirements:
  - hands-on ML experience
  - python
  - experience with at least 1 ML toolkit (e.g. sklearn, tensorflow, pytorch, etc)
  - masters or PhD with ML specialization
  - 2+ years of industry experience 
building ML systems
  - comfortable with both software engineering and data science
  - Previous startup work experience, or working in the early stages of a product’s lifecycle

Nice-to-have
  - experience with Deep Learning
  - experience with text understanding, entity recognition or other NLP
  - experience with distribution computation (pyspark, hadoop etc)


Why you’ll enjoy working at Abnormal Security:
  - Competitive pay and equity
  - Extremely challenging and equally rewarding career growth opportunities 
  - Amazing teammates to work with and learn from
  - Every team member will play a meaningful role in the company’s success
  - Medical, dental, vision health insurance benefits
  - Daily catered lunches

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