Principal Software Engineer, ML Infrastructure

About the Team:

The Machine Learning Infrastructure team is where cutting-edge technology meets real-world impact. We build a powerful, scalable foundation for our content recommendation engine, directly influencing the user experience. Working closely with ML, Product, and Data Science, we solve complex technical challenges to deliver innovative ML-powered solutions that delight millions.

About the Role:

As a Principal Engineer on the ML Infrastructure team, you will be a technical leader and visionary, driving the evolution of our machine learning platform. You will tackle the most complex and impactful technical challenges, shaping the architecture and technology choices that enable our ML capabilities to scale and deliver exceptional user experiences. You will be a key influencer, bridging the gap between engineering and product, and a mentor to senior engineers, fostering a culture of technical excellence and continuous improvement. Your work will be used by millions of users.

This is a hybrid role in our San Francisco office.

What You'll Do:

Technical Leadership & Strategy:

• Vision & Influence: Define and champion the long-term vision for ML infrastructure, aligning it with company goals and industry best practices. Influence technical direction and technology selection across the ML platform
• Strategic Roadmap: Develop and maintain a roadmap (6-12 months) for the ML Infra team, anticipating future needs and proactively addressing emerging trends
• Innovation & Optimization: Identify opportunities to improve ML infrastructure efficiency, scalability, and performance. Research and advocate for new technologies and approaches to optimize the ML development lifecycle

Architecture, Design & Engineering:

• System Design: Lead the architecture and design of complex ML systems, ensuring scalability, reliability, security, and maintainability
• Distributed Systems Expertise: Design and build scalable, high-throughput, and/or low-latency distributed systems using Scala and related technologies. This includes expertise in areas like distributed databases, message queues, and stream processing
• Quality & Standards: Champion and enforce engineering best practices, including code quality, testing, and documentation. Contribute to the development and implementation of ML infrastructure standards

Problem Solving & Delivery:

• Technical Problem Solving: Resolve critical and complex technical challenges related to ML infrastructure, demonstrating expertise in debugging, performance optimization, and system troubleshooting
• Project Execution: Lead and deliver complex ML infrastructure projects, effectively managing scope, timelines, and dependencies. Mentor engineers on project management best practices
• Collaboration & Mentorship: Foster a collaborative environment and provide technical mentorship to other engineers, enabling their growth and development

Communication & Collaboration:

• Cross-functional Partnership: Collaborate effectively with data scientists, ML engineers, and product managers to understand their needs and translate them into infrastructure solutions
• Stakeholder Management: Communicate effectively with stakeholders at all levels, including senior leadership. Clearly articulate technical concepts, progress updates, and roadblocks
• Knowledge Sharing: Promote knowledge sharing and best practices across the organization through documentation, presentations, and mentorship

Your Background:

• 10+ years of experience in software engineering, with a significant focus on building and scaling large-scale distributed systems
• Bachelor's or Master's degree in Computer Science or a related field
• Proven experience as a technical leader, architecting and designing complex systems, preferably in the ML infrastructure domain
• 5+ years of experience with databases, caching technologies, and message brokers
• Expertise in Scala, Java, Python programming languages
• Extensive experience with cloud platforms (preferably AWS)

Bonus:

• Experience in the media or streaming industry
• Contributions to open-source projects related to ML infrastructure

Pursuant to state and local pay disclosure requirements, the pay range for this role, with final offer amount dependent on education, skills, experience, and location is listed annually below. This role is also eligible for an annual discretionary bonus, long-term incentive plan, and various benefits including medical/dental/vision, insurance, a 401(k) plan, paid time off and other benefits in accordance with applicable plan documents.

California Compensation

Base ($246,000 to $352,000 / year) + Bonus + Long-Term Incentive Plan + Benefits

#LI-MQ1 #LI-Hybrid