29 Jan 2018

Full-Time Data Science Engineer

QuantiplySan Jose, California, United States

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Job Description

About Quantiply

Did you know that Money Laundering is a primary enabler of criminal activity like drug trafficking, smuggling, terrorism, and corruption around the world with $2.3 trillion estimated to be laundered annually? Criminals are becoming more and more sophisticated in rapidly innovating new ways to launder money and current methods of detecting money laundering are antiquated and ineffective. Quantiply’s Sensemaker application suite and platform solutions use AI and machine learning algorithms to identify money laundering and other criminal activities and automatically recommend mitigation strategies and actions. If you are looking for an opportunity to work on complex business problems using the latest AI and Machine Learning technologies, work with best and brightest in crafting innovative solutions while making a positive impact on society, Quantiply is the place for you.

Job Description

We’re looking for data science engineers with experience in machine learning and artificial intelligence. In this position, you will be responsible for analyzing and optimizing key deep learning (DL) and machine learning (ML) algorithms and applications on current and next generation hardware, including GPUs. In addition, responsibilities include working as part of a team that is collaborating on conceiving, researching, and prototyping new machine learning techniques and use cases with the goal of driving Quantiply’s growth in this space. This includes both ensuring that leading DL/ML frameworks (e.g., TensorFlow) are taking full advantage of features in our products, as well as, impacting next generation products by driving technologies to ensure performance leadership on emerging DL/ML applications and use cases. Ideal candidates will have a good understanding of state-of-the-art techniques in machine learning and deep learning, performance optimization, and benchmarking, along with a strong understanding of computer architecture. Candidates must also possess strong verbal and written communication skills and the demonstrated ability to work in a demanding team-oriented environment.

You are expected to maintain substantial knowledge of state-of-the-art principles and theories in the space of machine learning, performance optimization, and computer architecture in general. You may also participate in the development of intellectual property.

Qualifications

• At least 2 years of industry experience in Machine Learning
• At least 1 year experience in Big Data acquisition and enrichment
• Experience in Scala, Java, C++, Python, GoLang or other equivalent languages commonly, as well as, one or more frameworks like SparkML, TensorFlow
• Industry experience building and productionizing innovative end-to-end Machine Learning, text analytics, search, and entity graph systems
• Excellent understanding of common families of models, feature engineering, feature selection, and other practical machine learning issues, such as overfitting
• Excellent understanding of text analytics primitives and information extraction and integration techniques
• Applicants must be completely comfortable with Spark, Spark Streaming, and Scala at a minimum
• Experience with Hadoop, HBase, Cassandra, Kafka, and Solr is a plus
• Experience with graph databases
• Knowledge of ML pipeline frameworks, as well as, incremental model building and scoring, detection of model decay is a big plus
• Experience with deep learning, SAP HANA, SAP Vora, and Predictive Analytics Libraries is a big plus
• Experience with performance profiling, characterization, and optimization is also a big plus

How to Apply

Please use the apply button or submit resumes to Hiring@quantiply.com with a brief introduction.

Job Categories: Technology. Job Types: Full-Time. Job Tags: ai, analytics, artificial intelligence, big data, deep learning, financial services, fintech, machine learning, ml, regtech, reinforcement learning, tensorflow, and unsupervised learning. Salary: 100,000 and above.

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