machine learning siliconarmada
Software Engineer in Machine Learning/siliconarmada.com
Your mission We are searching for great machine learning engineers to join the team responsible for: · Extending Criteo's large scale distributed machine learning library (e.g., implementing new distributed and scalable machine learning algorithms, improving their performance) · Building and improving prediction models for ad targeting; proving the business value of the changes and deploying them to production · Gathering and analyzing data, performing statistical modeling You'll have the opportunity to work on highly challenging problems with both engineering and scientific aspects; for example: · Click prediction:ÂHow do you accurately predict in less than a millisecond if the user will click on an ad? Thankfully, you have billions of datapoints to help you. · Offline testing:ÂYou can always compute the classification error on a model predicting the click probability. But will it really correlate with the online performance of this model? · Explore / exploit:ÂIt's easy, UCB and Thomson sampling have low regret. But what happens when new products come and go and when each ad displayed changes the reward of each arm? But what do you do when all data are not equal and when you must distribute the learning overÂthousandsÂof nodes? To qualify for this mission, you need: · MS degree in Computer Science or related quantitative field with 3 years of relevant experience or Ph.D degree in Computer Science or related quantitative field · Good understanding of the mathematical foundations behind machine learning algorithms · Great coding skills.
Software Engineer - Machine Learning/siliconarmada.com
Software Engineer - Machine Learning New York Posted Mar 18, 2016 - Requisition No. 49181 Apply Now Our team is made up of data scientists and software engineers. It's common to see us gathered around a whiteboard solving difficult problems. We develop the machine learning models and infrastructure to support Bloomberg products in the areas of Law, Government and New Energy Finance. We extract knowledge from millions of legal documents and use it to build intelligent models with information retrieval, machine learning and natural language processing. This enables our customers to get the right answers - fast.