Python Programming, Scala Programming, C++, Java Programming, Machine learning techniques, Data science techniques, SQL, Apache Hadoop, MapReduce, TensorFlow, PyTorch, R Programming
At ASAPP, we are on a mission to build transformative machine learning-powered products that push the boundaries of artificial intelligence and customer experience. We focus on solving complex, data-rich problems — the kind where there are substantial systemic inefficiencies and where a real solution will have a significant economic impact. Our interaction platform uses machine learning across both voice and digital engagement channels to augment and automate human work, radically increasing productivity and improving the efficiency and effectiveness of customer experience teams.
We are looking for a new member to join our Machine Learning team as a Staff Machine Learning Engineer focused on Distributed Systems. You should have the passion to tackle tough problems by bringing your expertise to ASAPP to help us solve cutting edge machine learning and natural language processing (NLP) challenges.
As a part of our team, you will design, develop, and deploy large-scale machine learning training infrastructure and processes to simultaneously train and update hundreds or thousands of cutting-edge models at the same time. You’ll work closely with our researchers, site reliability engineers, data engineers, and fellow machine learning engineers to build systems capable of training machine learning models at a scale and quality required to serve our clients, the world’s largest companies. You’ll be faced with new technical challenges and things to learn about ML and software engineering on a daily basis.What you'll do
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Our artificial intelligence and machine learning products deliver automation and human augmentation, allowing individuals and organizations to realize their full potential. Today, the world's largest organizations rely on ASAPP to provide amazingly efficient and effective customer experiences. Our Research & Development team is unparalleled, driving the advancement of AI, machine learning, speech recognition, robotic process automation, natural