Description
We're looking for a Staff Machine Learning Engineer to join our Growth Content Science team, focusing on building and improving the ML models and systems that decide which content to bring to users on our growth surfaces, particularly notifications.
As a Staff Machine Learning Engineer, you'll lead the technical direction for notification content ranking, build complex models and systems, and set the bar for code quality and healthy ML infrastructure.
Responsibilities:
- Lead multiple technical sub-areas within Growth content science
- Drive Growth ML model improvements through AB test-driven innovation
- Own the health of our ML ecosystem, including training pipelines, feature and serving infrastructure, and monitoring
- Mentor junior engineers and help raise the technical excellence bar
- Collaborate with colleagues and stakeholders to tackle big initiatives
- Work closely with other engineering leaders to form technical directions and roadmaps
- Operate autonomously and take ownership in complex and evolving environments
- Identify and apply state-of-the-art techniques from recent research
- Continuously optimize various parts of work using cutting-edge AI tools
Requirements:
- Graduate degree in Computer Science or a related field
- Minimum of 8 years of experience in machine learning engineering
- Expertise in recommender modeling, including sequence modeling of user behavior with transformer architectures
- Experience building and operating high-QPS, latency-constrained ML systems
- Industry-grade software engineering experience
- Understanding of content personalization and content quality
- Experience leading technical work across teams and mentoring junior engineers
- Outstanding written and verbal communication skills
- Demonstrated experience using AI to improve speed and quality in applied research
- Strong track record of publications and patents
Benefits:
- Base salary range: $189,308-$389,753 USD
- Eligible for equity
In-office requirement: 1-2 times/quarter Relocation assistance: Not eligible