Senior Machine Learning Engineer

To be successful, candidates will need a machine learning background, proven software development skills, a love of learning. They will also need to be able to collaborate with multi-functional teams, including researchers, engineers, data scientists/analysts, and product managers, to help develop and implement machine learning algorithms and testing workflows. Collaborate with other MLEs to build scalable, production-ready ML solutions, taking algorithms from initial concept through to deployment. Give to the ongoing improvement of our ML infrastructure and tooling. Engage in continuous learning and development, staying up-to-date with the latest advances in machine learning and software engineering. Mentor junior MLEs on the team to ensure best practices are followed. Bachelorʼs degree in Computer Science, Statistics, Mathematics with equivalent experience. 5+ years of related experience building high throughput scalable applications or building machine learning models. Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and experience building distributed systems. Experience building data processing pipelines and large scale machine learning systems with experience in big data technologies like Spark, SQL, Snowflake/Hadoop, etc. Skilled in communication, problem solving, critical thinking Attention to detail, data accuracy and quality of output. PhD or Graduate degree with research/work experience using data science techniques (including but not limited to Computer Science, Statistics, Mathematics, etc). Experience in Recommender Systems, Personalization, Search, Computational Advertising or Natural Language Processing including RAG based Generative AI and transformer architecture. Skilled in communication, problem solving, critical thinking. Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning in real applications a plus. Experience with Spark, TensorFlow, Keras, and PyTorch a plus

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