Principal ML/AI Architect – AI for Member Systems (AIMS)
The Opportunity
At Netflix, our mission is to entertain the world by connecting members to a vast library of global stories. With over 270 million members in 190+ countries, our product helps people quickly find something great to watch. The AI for Member Systems (AIMS) organization sits at the core of this experience, building and operating the AI systems that power recommendations, personalization, search, discovery, and messaging. AIMS is also responsible for pushing the boundaries of Netflix Foundation models.
AIMS leverages advanced machine learning, Generative AI, and Large Language Models (LLMs) to deliver these experiences reliably and efficiently at global scale. As our systems’ complexity and ambition grow, we are investing in a stronger ML infrastructure and architectural foundation—shared capabilities, paved paths, and abstractions that accelerate the development of AI-powered member experiences.
We are seeking an ML Architect (L7) to provide deep technical leadership in this area. This senior individual contributor role focuses on shaping the ML infrastructure, patterns, and systems that AIMS builds upon—ensuring they are cohesive, scalable, and high-quality.
Responsibilities
Own the Architectural Vision for ML Infrastructure:
Define and evolve the core architecture for AIMS’ AI foundations, including data and feature pipelines, training and evaluation workflows, online inference and serving, and shared services for recommendations, search, discovery, and messaging.
Architect Paved Paths for AI Product Teams:
Design the “paved road” for AIMS teams to build and deploy ML models and GenAI capabilities, enabling fast iteration while benefiting from consistent patterns in data access, training, evaluation, rollout, and monitoring.
Sequence and Layer ML Capabilities Thoughtfully:
Architect how different layers of ML capability (e.g., embeddings and retrieval, ranking and personalization, LLM/GenAI components, evaluation and safety) fit together over time. Make intentional decisions about centralizing vs. decentralizing capabilities.
Create Reusable, Horizontal ML Components:
Design new capabilities (e.g., representation services, evaluation frameworks, LLM-powered features) as reusable building blocks that can be extended across multiple member experiences, avoiding silos.
Scope and De-risk New Architectural Directions:
Explore new technical directions through prototypes and proofs of concept, especially where optimal abstractions are not yet clear. Use hands-on work to validate approaches and inform long-term decisions.
Connect Dots Across AIMS Verticals:
Understand how different AIMS pillars (Recommendations, Search & Discovery, Evidence/Evaluation, LLMs/Foundations, Messaging) use and extend ML infrastructure, identifying opportunities to consolidate, simplify, or generalize solutions.
Shape Requirements with Platform and Infra Partners:
Advocate for AIMS’ ML infrastructure needs with platform and infrastructure teams. Translate requirements into actionable capabilities and ensure architectural alignment with broader Netflix platforms.
Champion Technical Excellence and Best Practices:
Raise the bar on reliability, observability, performance, and cost-effectiveness of AIMS’ ML systems. Guide standards and practices (e.g., evaluation, rollout, guardrails) and mentor senior engineers across teams.
What We’re Looking For
Deep Experience with Large-Scale ML Infrastructure:
Significant experience designing and building ML systems in production, including data pipelines, training/evaluation workflows, and online serving for high-traffic, ML-driven products.
Fluency with Modern ML and GenAI Patterns:
Strong working knowledge of contemporary ML approaches, such as recommendation/ranking systems and LLM/GenAI applications. Able to design infrastructure that supports these models effectively.
Hands-On Ability to Scope and Validate Architectures:
Capable of independently building prototypes, exploring new technologies, and turning ambiguous problems into concrete architectural proposals and reference implementations.
Strength in Abstraction, Frameworks, and Reuse:
Proven ability to identify common patterns and design frameworks/abstractions that are flexible, extensible, and easy for engineers to adopt.
Ability to Influence Technical Direction Across Teams:
Comfortable working with and influencing senior engineers and leaders across multiple teams. Skilled at building consensus and guiding complex trade-offs without formal authority.
Comfort in a Fast-Moving, High-Context Environment:
Thrives in a setting with high autonomy and expectations. Navigates ambiguity, makes informed bets, and iterates quickly to optimize AI’s impact for members.
Compensation
Our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $310,000 - $1,870,000.
About the job
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Principal ML/AI Architect – AI for Member Systems (AIMS)
The Opportunity
At Netflix, our mission is to entertain the world by connecting members to a vast library of global stories. With over 270 million members in 190+ countries, our product helps people quickly find something great to watch. The AI for Member Systems (AIMS) organization sits at the core of this experience, building and operating the AI systems that power recommendations, personalization, search, discovery, and messaging. AIMS is also responsible for pushing the boundaries of Netflix Foundation models.
AIMS leverages advanced machine learning, Generative AI, and Large Language Models (LLMs) to deliver these experiences reliably and efficiently at global scale. As our systems’ complexity and ambition grow, we are investing in a stronger ML infrastructure and architectural foundation—shared capabilities, paved paths, and abstractions that accelerate the development of AI-powered member experiences.
We are seeking an ML Architect (L7) to provide deep technical leadership in this area. This senior individual contributor role focuses on shaping the ML infrastructure, patterns, and systems that AIMS builds upon—ensuring they are cohesive, scalable, and high-quality.
Responsibilities
Own the Architectural Vision for ML Infrastructure:
Define and evolve the core architecture for AIMS’ AI foundations, including data and feature pipelines, training and evaluation workflows, online inference and serving, and shared services for recommendations, search, discovery, and messaging.
Architect Paved Paths for AI Product Teams:
Design the “paved road” for AIMS teams to build and deploy ML models and GenAI capabilities, enabling fast iteration while benefiting from consistent patterns in data access, training, evaluation, rollout, and monitoring.
Sequence and Layer ML Capabilities Thoughtfully:
Architect how different layers of ML capability (e.g., embeddings and retrieval, ranking and personalization, LLM/GenAI components, evaluation and safety) fit together over time. Make intentional decisions about centralizing vs. decentralizing capabilities.
Create Reusable, Horizontal ML Components:
Design new capabilities (e.g., representation services, evaluation frameworks, LLM-powered features) as reusable building blocks that can be extended across multiple member experiences, avoiding silos.
Scope and De-risk New Architectural Directions:
Explore new technical directions through prototypes and proofs of concept, especially where optimal abstractions are not yet clear. Use hands-on work to validate approaches and inform long-term decisions.
Connect Dots Across AIMS Verticals:
Understand how different AIMS pillars (Recommendations, Search & Discovery, Evidence/Evaluation, LLMs/Foundations, Messaging) use and extend ML infrastructure, identifying opportunities to consolidate, simplify, or generalize solutions.
Shape Requirements with Platform and Infra Partners:
Advocate for AIMS’ ML infrastructure needs with platform and infrastructure teams. Translate requirements into actionable capabilities and ensure architectural alignment with broader Netflix platforms.
Champion Technical Excellence and Best Practices:
Raise the bar on reliability, observability, performance, and cost-effectiveness of AIMS’ ML systems. Guide standards and practices (e.g., evaluation, rollout, guardrails) and mentor senior engineers across teams.
What We’re Looking For
Deep Experience with Large-Scale ML Infrastructure:
Significant experience designing and building ML systems in production, including data pipelines, training/evaluation workflows, and online serving for high-traffic, ML-driven products.
Fluency with Modern ML and GenAI Patterns:
Strong working knowledge of contemporary ML approaches, such as recommendation/ranking systems and LLM/GenAI applications. Able to design infrastructure that supports these models effectively.
Hands-On Ability to Scope and Validate Architectures:
Capable of independently building prototypes, exploring new technologies, and turning ambiguous problems into concrete architectural proposals and reference implementations.
Strength in Abstraction, Frameworks, and Reuse:
Proven ability to identify common patterns and design frameworks/abstractions that are flexible, extensible, and easy for engineers to adopt.
Ability to Influence Technical Direction Across Teams:
Comfortable working with and influencing senior engineers and leaders across multiple teams. Skilled at building consensus and guiding complex trade-offs without formal authority.
Comfort in a Fast-Moving, High-Context Environment:
Thrives in a setting with high autonomy and expectations. Navigates ambiguity, makes informed bets, and iterates quickly to optimize AI’s impact for members.
Compensation
Our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $310,000 - $1,870,000.