Software Engineer L5 - Consumer ML Core

Key Skills

Aartificial intelligence, API, Data Migration, Machine learning techniques, Operations, Streaming APIs

Job Description

With more than 230 million members in over 190 countries, Netflix continues to shape the future of entertainment around the world. Machine Learning/Artificial Intelligence is powering innovation, from personalization for members, to optimizing our payment processing and other revenue-focused initiatives.

The Machine Learning Platform (MLP) department provides the foundation for all of this innovation. It offers ML/AI practitioners across Netflix the means to achieve the highest possible impact with their work by making it easy to develop, deploy and improve their machine learning models. 

As part of our mission to support the infrastructure for machine learning, we are hiring a Software Engineer to join the Consumer ML Core team with a focus on our in-house fact store, offline data processing & feature generation tools and cluster integrations for large-scale Spark computing jobs.

In this role, you will:

• Solve complex and cross-cutting challenges for data enablement that allow ML researchers to leverage new data sources in their research and improve performance for backfilling & generating data for ML workflows.
• Identify and resolve user pain points and user experience improvement areas by building and improving tools for offline feature generation, online fact logging, and integration points for model training and evaluation metrics.
• Proactively identify migration, secure access, operational and support requirements. Serve as a leading contributor to operational excellence for the team.
• Ramp up and join the team’s on-call rotation to ensure system stability and timely user support.
• Leverage your experience and judgment to identify system improvements, tech debt elimination opportunities, and future integrations that evolve the platform for ever-growing research data needs.

What we offer:

• Opportunity for impact. We are not seeking someone to assimilate into the way things have always been done. Your voice, experience, and technical opinion will have significant weight in team decisions. Our product is used by several dozen ML researchers and hundreds of ML pipelines. Your work will have high visibility and opportunity for new capability enablement, compute & storage cost improvement, performance wins, and tools for better research user experience.
• Responsibility. Netflix offers true transparency and autonomy. Our culture is unique and is key to how we innovate. You will be given high-level descriptions of the problems our users most need you to solve and given the space and freedom to drive solutions.
• Learning and Growth. You will be creating ML developer tools and user experiences that have never been done before. You will have the opportunity to work with stunning colleagues who value collaboration and have a wealth of experience you can tap into for support, guidance, and partnership. You can grow your career and find the areas you are passionate about by exploring what ML Platform offers across a wide variety of projects.

Who will be successful in this role?

• You are highly customer-driven and empathic. You strive to always focus on delivering business value with an excellent customer service mentality.
• You have a track record of delivering solutions that your stakeholders love. You drive development & operational success from planning to implementation to delivery.
• You are eager to go deep and wide on ML-facing projects. When a project needs deep technical expertise in a domain area, you are able to get up to speed quickly. When projects require breadth of focus, you are eager to do what’s needed to deliver value even if it means going outside of your comfort zone.

Technical Requirements

• Significant individual contributor and project-leading experience in building big data systems and feature engineering frameworks, including experience with JVM technologies and Spark.
• Experience operating high throughput online data processing services & time-sensitive offline data processing pipelines, handling late arriving data, managing schema compatibility, debugging data query performance, and recovering from data outages.
• Experience working in on-call rotations supporting customers, responding to system outages, and developing incident retrospective materials to learn and improve from failures. Our system does not traditionally have a high on-call burden, but team expectations include participating in operational support to ensure the system keeps running smoothly and responding proactively to user requests for support on bugs, unexpected errors, and usability challenges.
• Software design and user-facing API development experience, such as creating and maintaining client libraries for logging and querying data from data platform systems.

Skills

• Demonstrated experience in software development for complex data-driven applications and machine learning systems (prior experience in feature stores, fact stores or ML-facing data engineering is a strong plus).
• Strong technical writing ability (RFCs, memos, technical presentations). Ability to motivate shared buy-in and understanding. Ability to drive pragmatic decisions and disagree & commit when necessary. Empathic approach to collaboration and learning from mistakes.
• Advocacy for operational best practices and experience establishing necessary observability, logging, telemetry, reporting and on-call processes to support engineering excellence.
• Experience judging trade-offs between priorities, speed of delivery, tech debt and architectural complexity. Proactive approach to tracking project status, keeping stakeholders and teammates informed, and striking a good balance between process overhead and efficiency.
• Experience (or strong interest in) designing developer tools, CLIs, and APIs that interact with complex user workflows and backend systems, especially for end-to-end workflows that generate feature data for large ML pipelines.

At Netflix, we carefully consider a wide range of compensation factors to determine your personal top of market. We rely on market indicators to determine compensation and consider your specific job, skills, and experience to get it right. These considerations can cause your compensation to vary and will also be dependent on your location. The overall market range for roles in this area of Netflix is typically $100,000 - $700,000. 

This market range is based on total compensation (vs. only base salary), which is in line with our compensation philosophy. Netflix is a unique culture and environment. Learn more here.