Senior Engineering Manager - Machine Learning

Job not on LinkedIn

March 25

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Logo of MIND

MIND

MIND is on a mission to help organizations thrive in a digital world by protecting their most sensitive information. MIND is the first-ever data security platform that puts data loss prevention (DLP) and insider risk management (IRM) programs on autopilot to automatically protect sensitive information, mitigate risk and preserve brand reputation. We enable businesses to mind what really matters—their most sensitive data. Founded and led by cybersecurity leaders and industry veterans, MIND is based out of Seattle, WA. For more information, contact us at info@mind.io.

11 - 50 employees

📋 Description

•Build and operate the tools we use as well as the infrastructure to label data, create features, train, evaluate and serve both online and offline models. •Build and lead a team of highly-engaged engineers by hiring, coaching, and instilling a sense of ownership and impact. •Build the vision and roadmap for the Machine Learning team by working with your team and partners across the company. •Manage processes and use your technical expertise to continually ensure that your team achieves extraordinary results. •Work with other Engineering Managers to continuously improve the Engineering organization and uphold our workplace philosophy.

🎯 Requirements

•You have 5+ years of experience as a Software Engineer. •You have 5+ years of experience as an Engineering Manager and successfully managed a team of 5+ Software Engineers and Technical Leads or Managers. •You're a mentor, storyteller, and you're great at coordinating with a variety of teams throughout the company. •You excel in undefined environments and get excited about finding solutions to complex technical challenges, and then building them. •You enjoy coming up with pragmatic solutions to concrete problems using first principles thinking. •You've worked with complex distributed machine learning systems deployed at scale. •You keep up with the industry trends and continuously identify new tools to use to solve technical problems.

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