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Your responsibilities will include designing end-to-end model lifecycle patterns (MLOps) to boost velocity of development for ML engineers, zero-to-one development and support of a graph ML codebase and platform, collaborating with ML engineers on performance tuning, optimizing batch data processing, and architecting pipelines to build and maintain massive graph data structures.</p>\n<p>We are looking for an experienced engineer with 8+ years of experience in ML infrastructure, including model training and model deployments. You should have hands-on experience with ML optimization, cloud-based technologies, MLOps tools, and proficiency with common programming languages and frameworks of ML. Strong focus on scalability, reliability, performance, and ease of use is essential.</p>\n<p>In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. 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