Machine Learning Engineer, Trust and Safety

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In this role you will:

• Build and maintain systems that enable the T&S team to detect and remediate bad actors on the platform. You will use techniques that spread across many ML fields: Deep Learning, Anomaly Detection, Qualitative/Quantitative Analytics, etc and will leverage large amounts of text, photos, and app behavior data. 
• You will integrate closely with T&S policy, product, and engineering teams. You will be responsible for proposing new algorithms and get them integrated into the T&S ecosystem.
• Collaborate with policy, and the product team to establish how an algorithm will be used.
• Collaborate with engineering teams to put the algorithm in production.

Who you are:

• Successful candidates will have a learning mindset, care about problems more than the technique, are self-motivated, and collaborative.
• Experience with at least one popular machine learning framework. Preferably Tensorflow.
• Experience with modern machine learning techniques. Preferably Supervised Learning using Deep Learning, and Anomaly Detection.
• Experience with modeling text, and photos data.
• Experience with Qualitative/Quantitative analytics at scale. Preferably using modern tools like Spark.

Qualifications:

• BS/MS/Ph.D in Computer Science or related field.
• Proficiency in at least one popular programming language. Preferably Python.
• Working knowledge of AWS, Kubernetes, and Docker.
• 1+ years of professional experience developing, and deploying ML models.