Build and maintain scalable machine learning solutions in production environments; Train and validate mostly statistical-based models considering use-case, complexity, performance, and robustness; Develop a deep understanding of the “why” behind our models & systems; Partner with product managers, tech leads, and stakeholders to analyze business problems, clarify requirements and define the scope of the systems needed; Participate in the development backlog grooming and estimation processes; Contribute to the solution design and feature ideas, betterments; Work with data platform teams to build robust scalable batch and realtime data pipelines
Requirements:
Bachelor's degree in Computer Science, Engineering or a related field, or equivalent training, fellowship, or work experience; 3+ years of applied ML experience; Solid background in the foundations of machine learning; Track record of building, shipping and maintaining machine learning models in production; Track record of designing and architecting experiments and analysis to inform product roadmap; Understanding of frameworks like PyTorch, TensorFlow, or Keras, what and how these frameworks do what they do
Text:
Machine Learning Engineer Build and maintain scalable machine learning solutions in production environments; Train and validate mostly statistical-based models considering use-case, complexity, performance, and robustness; Develop a deep understanding of the “why” behind our models & systems; Partner with product managers, tech leads, and stakeholders to analyze business problems, clarify requirements and define the scope of the systems needed; Participate in the development backlog grooming and estimation processes; Contribute to the solution design and feature ideas, betterments; Work with data platform teams to build robust scalable batch and realtime data pipelines Bachelor's degree in Computer Science, Engineering or a related field, or equivalent training, fellowship, or work experience; 3+ years of applied ML experience; Solid background in the foundations of machine learning; Track record of building, shipping and maintaining machine learning models in production; Track record of designing and architecting experiments and analysis to inform product roadmap; Understanding of frameworks like PyTorch, TensorFlow, or Keras, what and how these frameworks do what they do
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