Senior Machine Learning Engineering Manager

Yesterday

🏄 California – Remote

Although this job is listed in California, this company may be open to hiring remote in other states.

+3 more states

🏄 California – Remote 🗽 New York – Remote 🤠 Texas – Remote ☕ Washington – Remote

💵 $190.3k - $305.6k / year

⏰ Full Time

🟠 Senior

👮‍♀️ Software Engineering Manager

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Atlassian

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Atlassian is a software company known for its collaboration and productivity tools designed to help teams manage projects and workflows effectively. One of its flagship products, Trello, offers a user-friendly interface for organizing tasks, tracking progress, and streamlining communication across various teams. With features such as automation, integration with popular apps, and customizable boards, Atlassian aims to enhance team collaboration and increase productivity across diverse sectors.

b2b enterprise software • bug tracker • issue tracker • enterprise wiki • corporate wiki

10,000+ employees

⚡ Productivity

☁️ SaaS

🏢 Enterprise

💰 $3.2G Secondary Market on 2014-04

📋 Description

• Manage the end-to-end machine learning lifecycle, from data collection and preprocessing, to model development and deployment, to evaluation and monitoring. • Research and implement novel machine learning techniques and algorithms that can improve the performance, scalability, and robustness of our Recommendation system, and other AI/ML models. • Mentor and coach your team members on best practices, code quality, design patterns, testing, debugging, and documentation. • Hire, onboard, and retain top talent for your team and foster a culture of innovation, collaboration, and excellence. • Communicate effectively with internal and external partners, present technical concepts and results clearly and concisely, and solicit feedback and input from various stakeholders.

🎯 Requirements

• Master or PhD in a quantitative subject (Computer Science, Mathematics, Statistics, Operations Research, or relevant work experience) • 5+ years of experience managing machine learning engineering teams running core services at scale • Experience building and scaling machine learning models in business applications using large amounts of data • Ability to communicate and explain data science concepts to diverse audiences, craft a compelling story • Focus on business practicality and the 80/20 rule; very high bar for output quality, but recognize the business benefit of "having something now" vs "perfection sometime in the future" • Agile development mindset, appreciating the benefit of constant iteration and improvement

🏖️ Benefits

• health coverage • paid volunteer days • wellness resources • and so much more