Define and lead the strategic roadmap for the Machine Learning Engineering team, aligning with broader organizational goals; Recruit, build, and lead a high-performing team of Machine Learning Engineers and Scientists; Establish and maintain engineering best practices for ML model development, deployment, and operation (MLOps); Oversee the design, development, and deployment of production-grade ML solutions across various business domains; Collaborate with data scientists, product managers, and other stakeholders to understand business needs and translate them into technical requirements
Requirements:
Master's degree in Computer Science, Data Science, or related field (PhD preferred); 10+ years of experience in leading and managing software engineering teams; 5+ years of experience working with machine learning scientists and engineering and deploying models to production; Proven track record of successfully delivering impactful ML solutions within a business context; Strong understanding of the ML engineering lifecycle, including model development, deployment, monitoring, and governance
Text:
Sr. Mgr, Machine Learning Define and lead the strategic roadmap for the Machine Learning Engineering team, aligning with broader organizational goals; Recruit, build, and lead a high-performing team of Machine Learning Engineers and Scientists; Establish and maintain engineering best practices for ML model development, deployment, and operation (MLOps); Oversee the design, development, and deployment of production-grade ML solutions across various business domains; Collaborate with data scientists, product managers, and other stakeholders to understand business needs and translate them into technical requirements Master's degree in Computer Science, Data Science, or related field (PhD preferred); 10+ years of experience in leading and managing software engineering teams; 5+ years of experience working with machine learning scientists and engineering and deploying models to production; Proven track record of successfully delivering impactful ML solutions within a business context; Strong understanding of the ML engineering lifecycle, including model development, deployment, monitoring, and governance
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