Salesforce.com, Inc Lead or Principal Machine Learning Engineer, Philanthropy Cloud Einstein in San Francisco, California
Job CategoryFoundation - Tech and Products Group
Machine Learning Engineer, Philanthropy Cloud EinsteinMachine Learning Engineering for Social Impact - This is a dream job if you want to make a positive impact in the world through your Engineering and Machine Learning skills.Salesforce.org is a nonprofit social enterprise with a mission to empower its community of stakeholders to accelerate impact in a whole new way. Salesforce.org impacts thousands of organizations and the millions of people they serve by delivering the world's best nonprofit and educational technology solutions at affordable rates. It also inspires employee giving by matching their donations and driving volunteer engagement in the community. And it leverages a unique self-sustaining model to generously re-invest the revenue generated back into the community through strategic grants focused on education and workforce development.Position DescriptionSalesforce Philanthropy Cloud is a brand new social impact platform to engage an army of citizen philanthropists. We are seeking a passionate engineer to help build from the ground up as we embark on building the next generation of technology for nonprofits and their corporate partners. The Machine Learning team builds large-scale recommendation systems on top of edge-cutting technologies. It also implements algorithms that drive personalization in mass scale, connecting corporations with charities and helping everyone discover great content and charity opportunities.ResponsibilitiesHere are some examples:
Develop, and contribute to, open source ML systems such as Apache PredictionIO to train and serve models
Build large-scale data pipelines and computation systems that process massive amount of data on Spark and EMR
Implement, and fine-tune, new personalization algorithms with various machine learning and deep learning techniques for targeted goals
Collect and process both batch and streaming data for feature engineering
Develop responsive web services that serve contextual recommendations
Create systems to accelerate offline experimentation and online A/B tests
Analyze and discover insights from user behaviors
5+ years of experience with hands-on, server side development
Expertise in JVM based languages (Java, Scala)
Deep Experience in building products on some production-grade systems such as Spark, Kafka, HBase and Kubernetes
Good understanding of applying machine learning algorithm libraries such as SparkML, Tensorflow and Mahout to personalization problems
Experience in building software on AWS cloud computing such as EMR and S3 and Heroku
Hands on expertise with search engines such as Elasticsearch
Experience in designing and developing of RESTful web services
Familiar with AB/Testing frameworks
Strong foundation in the mathematics and statistics behind machine learning techniques such as collaborative filtering, co-occurrence matrix and natural language processing
If hired, a Form I-9, Employment Eligibility Verification, must be completed at the start of employment.
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