Senior ML Platform Engineer (MLOps)

September 11

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Tripadvisor, the world's largest travel guidance platform*, helps hundreds of millions of people each month** become better travelers, from planning to booking to taking a trip$1. .$1

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1001 - 5000

💰 $300M Post-IPO Equity on 2021-03

Description

• Lead the development of scalable and efficient machine learning platform products and infrastructure • Develop technical specifications and architectures for new ML platform features and products • Collaborate with cross-functional teams of engineers, data scientists, and product stakeholders across the globe to ensure product and infrastructure development aligns with business goals • Define and enforce engineering best practices to ensure high-quality deliverables • Participate in the code review process to ensure our code quality standards are met • Stay up-to-date with the latest ML platform technologies and trends to identify opportunities for product innovation • Participate in the hiring and onboarding process for new team members • Communicate effectively with technical and non-technical stakeholders to ensure alignment on project goals and timelines.

Requirements

• You have a BS or MS in Computer Science or equivalent • 8+ years of experience of commercial software development • Demonstrated excellence participating on cross functional teams in fast-paced environments, both in terms of technical leadership and hands-on coding. • Excellent ability to break down complex problems into simple solutions • Willingness and ability to learn, evaluate, and make recommendations for leveraging new technologies. • Strong analytical skills and desire to write clean, correct and efficient code. • Sense of ownership, urgency and pride in your work. • Proven that you are a leader who prioritizes, communicates clearly, and partners effectively with both technical and non-technical employees. • Excellent command of tools and expertise for troubleshooting production issues. • Experience working with Python, Docker, Kubernetes • Exposure to Machine Learning practices and platforms • Experience with Kubeflow, Seldon, Spark and AWS cloud service experience is a plus.