Software Engineer, Generative AI Media, Vertex AI

Google • Sunnyvale, CA

9d

About The Position

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

Our team sits at the architectural core of Google Cloud’s enterprise creative AI strategy. We are the experts transforming generative models into bespoke, high-performance engines for global enterprise customers. By fusing Google’s premier video and image foundation models with proprietary data, we address the industry’s post-training issues from Multimodal Supervised Fine-Tuning (SFT) to Latent Distillation to ensure customers can generate brand-aligned, production-grade media at scale.

The Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries. We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community. We also collaborate with product teams to bring innovations to real-world impact that benefits our customers.

Requirements

• Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages (e.g., Python, C++, Java), or 1 year of experience with an advanced degree.
• 1 year of experience with one or more of the following: speech/audio, reinforcement learning, ML infrastructure, or specialization in another ML field (e.g., computer vision, generative modeling).
• 1 year of experience with ML infrastructure (e.g., deployment, evaluation, optimization) using PyTorch, JAX, or TensorFlow.
• Experience analyzing large-scale datasets and utilizing ML pipelines to improve model performance and output quality.

Nice To Haves

• Master's degree or PhD in Computer Science, Artificial Intelligence, or related technical fields with a focus on Generative AI.
• 2 years of experience with data structures and algorithms, specifically applied to optimizing machine learning workloads or high-dimensional data processing.
• Experience in developing or fine-tuning Generative AI Media (e.g., image/video) models, including techniques like Latent Distillation or LoRA adaptation.
• Experience developing accessible technologies or tools that ensure safety within AI-generated content.
• Excellent verbal and written English communication skills, with the ability to translate complex ML concepts into actionable technical strategies for stakeholders.

Responsibilities

• Write product or system development code to build and scale advanced generative media (e.g., image and video) customization features within the Vertex AI ecosystem.
• Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback to empower enterprise AI developers.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality for large-scale GPU/TPU clusters.
• Implement solutions in one or more specialized ML areas (e.g., diffusion models or multimodal SFT), utilize ML infrastructure, and contribute to model optimization and data processing for high-fidelity media generation.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level