Machine Learning Engineer

Machine Learning Engineer Responsibilities Research, design, develop, and test operating systems-level software, compilers, and network distribution software for massive social data and prediction problems. Have industry experience working on a range of ranking, classification, recommendation, and optimization problems, such as payment fraud, click-through or conversion rate prediction, click-fraud detection, ads/feed/search ranking, text/sentiment classification, collaborative filtering/recommendation, or spam detection. Working on problems of moderate scope, develop highly scalable systems, algorithms and tools leveraging deep learning, data regression, and rules-based models. Suggest, collect, analyze and synthesize requirements and bottleneck in technology, systems, and tools. Develop solutions that iterate orders of magnitude with a higher efficiency, efficiently leverage orders of magnitude and more data, and explore state-of-the art deep learning techniques. Receiving general instruction from supervisor, code deliverables in tandem with the engineering team. Collaborate with DevOps team to develop and deploy machine learning models into production environments and ensure smooth operation of machine learning models in production. Work with data engineers to design and implement data pipelines for large-scale machine learning tasks. Collaborate with cross-functional teams to integrate machine learning models into larger systems. Participate in code reviews and ensure that all solutions are aligned with industry standards and best practices. Work with data scientists to analyze and interpret model performance metrics.