Software Engineer III, GenAI Data Operations Research, XR

Software Engineer III, GenAI Data Operations Research, XR Overview

As a Software Engineer in the GenAI Data Operations Research team, you will play a pivotal role in architecting and scaling the infrastructure necessary for GenAI data generation and inference tasks. Your responsibilities will include developing production-ready pipelines for large-scale data processing, running and monitoring deep learning experiments, and leveraging JAX to create end-to-end pipelines for fine-tuning foundational models.

Your work will contribute to delivering synthetic datasets for key Android XR projects, while also integrating and enhancing human-centric generative pipelines. You will be tasked with implementing automated evaluation tools and filtering stages to ensure data diversity and quality, effectively bridging the gap between advanced research and production-ready applications.

Responsibilities

• Design and implement scalable infrastructure and modular toolkits for large-scale distributed data processing, GenAI data generation, and metadata extraction.
• Oversee, monitor, and scale deep learning experiments across compute clusters, while developing efficient inference pipelines utilizing JAX.
• Lead the creation of high-volume synthetic datasets, including metadata deliveries for XR and device-related projects.
• Integrate automated evaluation and filtering tools to assess domain gaps and ensure the production of high-quality, photorealistic data.
• Transition pipelines to specialized hardware accelerators, such as TPUs or GPUs, to optimize production-scale inference.

Requirements

• A Bachelor’s degree or equivalent practical experience is required.
• At least 2 years of experience in software development using one or more programming languages, or 1 year of experience with an advanced degree.
• Minimum of 1 year of experience in areas such as speech/audio technology, reinforcement learning, ML infrastructure, or another specialization in machine learning.
• At least 1 year of experience with ML infrastructure, including model deployment, evaluation, data processing, and debugging.
• Preferred qualifications include a Master’s degree or PhD in Computer Science or a related technical field.
• Experience in designing infrastructure for bulk inference and metadata extraction is advantageous.
• Familiarity with human-centric generative pipelines is a plus.
• Proficiency in Python and experience with frameworks for large-scale data processing are essential.
• Ability to enable end-to-end fine-tuning for foundational GenAI models and optimize them for production environments, including specialized hardware like TPUs.

Benefits

• Opportunity to work on next-generation technologies that impact billions of users.
• Access to a collaborative and innovative work environment.
• Possibility to switch teams and projects as the business evolves.
• Engagement in projects that bridge advanced research and production-ready applications.

Degree Requirement: Not Specified

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