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The machine learning platform (MLP) at Discord is responsible for the end to end model lifecycle across all ML applications. We sit at the intersection of machine learning engineers (MLEs), core infrastructure, and ML consumers to provide tools, capabilities, and services that make machine learning easy, safe, and widely accessible. In this role, you will lead a high-performing team of engineers as you build, extend, and maintain critical ML systems that power everything from user facing recommendations and safety to revenue optimization and business insights. This role reports to our Senior Director of AI and Machine Learning, Chris Harland.

What You'll Be Doing

• Drive engineering execution within the MLP team on a regular basis
• Craft, communicate, and execute on the team’s vision and roadmap in partnership with our platform PM
• Collaborate with core infrastructure and data platform to make sound, first-principle decisions
• Partner with product engineering teams to ensure high quality, efficient delivery of model outputs into production
• Work closely with MLEs to create an ergonomic workflow as a paved path that maintains some flexibility
• Act as a strong summarizer that is able to make tradeoffs among priorities to ensure consistent, high-quality deliver

What you should have

• 3+ years of experience managing a team of engineers delivering data products
• 5+ years of experience as a software or machine learning engineer
• Demonstrated experience building ML products from 0 -> 1
• Strong execution skills to keep work on track
• A healthy balance between digging into code/architecture and leading through others
• A bias towards quantitative measure of progress and performance
• Demonstrated experience managing and growing engineers up to and through the staff level

#LI-Remote

The US base salary range for this full-time position is $290,000 to $318,800 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.