Principal Software Engineer, ML & Media Infra

Description

The ML & Media Infrastructure team makes delivering AI and ML solutions across the Ads and Core products fast, safe and efficient.

The team builds unified data, training, feature and inference infrastructure, and owns the platforms for content acquisition, media ingestion and media signal processing.

It works with several partner teams to bring strong inspiration content into the company, uses LLMs and VLMs in a near real-time system to understand content and build signals for LLM work, and meets GenAI compliance requirements.

This role sets technical direction for model training and serving, with a focus on GPU efficiency and large-scale ranking systems.

The company serves millions of people who come to find creative ideas and plan for the future.

The company uses AI as a partner in its work and in its hiring; interviews focus on how you explain your approach and think, and you can read more about its AI interview approach online.

Responsibilities

• Set the technical vision and roadmap for model training and serving, including reusable interfaces to data and feature infrastructure.
• Lead architecture for distributed training, fine-tuning, distillation, evaluation, and high-scale CPU and GPU inference.
• Lead architecture for content acquisition, media ingestion and signal processing.
• Improve efficiency across data loading, distributed execution, GPU kernels and memory, compilation, quantization, scheduling and capacity.
• Build reliable, observable platforms that guarantee quality and keep training and serving consistent.
• Work with Ads and Core AI/ML teams to ship features and models safely at the company scale.
• Drive cross-organization architecture decisions, migrations and operational standards, and mentor senior engineers to raise the engineering bar.
• Work closely with the Content, Shopping catalog and GenAI teams to improve the content ecosystem.
• Use AI-assisted development and analysis to speed up prototyping, performance diagnosis and validation, while keeping correctness and data safeguards strict.

Requirements

• You have set technical strategy and delivered company-wide infrastructure initiatives in ambiguous settings.
• You have deep experience with distributed ML systems, including production large-scale training and online inference.
• You have strong GPU performance skills, such as profiling, distributed execution, kernel and memory tuning, compilation or quantization.
• You have worked on AI/ML modeling, recommender systems, Ads ranking, retrieval, feature platforms or similarly demanding ML workloads.
• You have experience with content acquisition, such as crawlers, content understanding or NRT data processing.
• You have experience with search and recommendation systems or ads serving systems.
• You have strong systems programming and design skills in C++, Java or Python.
• You take high ownership and use sound judgment on reliability, security, cost and operational excellence.
• You use AI to work faster and critically evaluate AI-assisted output, taking responsibility for correctness, quality and sensitive data.
• You hold a Bachelor's degree in Computer Science, Engineering or a related field, or have equivalent experience.

Conditions

Base salary range is $285,452 - $449,541 USD. Final pay depends on factors such as location, travel, relevant prior experience and specific skills.

The role is eligible for equity.

Applicants must be based in the US.

This position is not eligible for relocation assistance. See the PinFlex page for details on the working model.

The role needs in-office attendance for in-person collaboration 1, 2 times per quarter, so you must live within commuting distance of the Palo Alto, CA or San Francisco, CA office.

The company aims for an equitable, inclusive workplace; the culture and benefits details are available online.