Staff Software Engineer, Applied AI

Google DeepMind; Singapore; On-site; SGD 100,000 - 140,000; Full time

Job summary

A leading AI research company in Singapore is seeking a Staff Applied AI Engineer to lead the development of novel applications leveraging generative AI models. This role requires a strong software engineering background with at least 8 years of experience in software development. The ideal candidate is passionate about building software products in fast-paced environments and has proven capabilities in testing and launching software. Join us to make a significant impact by translating cutting-edge AI research into real-world applications.

Qualifications

• 8 years of experience in software development.
• 5 years of experience testing and launching software products.
• 5 years leading ML design and optimizing ML infrastructure.

Responsibilities

• Design and develop scalable software applications leveraging generative AI models.
• Rapidly prototype new features and iterate based on evaluation results.
• Collaborate with researchers and product managers.

Skills

Software development

Generative AI

Prototyping

Collaboration

Education

Bachelor degree in computer science or equivalent

Tools

Python

TensorFlow

PyTorch

Google Cloud Platform

Job description

We are seeking a Staff Applied AI Engineer to lead the development and deployment of novel applications, leveraging Google’s generative AI models. This role focuses on rapidly developing new features, and working across partner teams to deliver solutions, and maximize impact for Google & top Google customers. You will be instrumental in translating cutting-edge AI research into real-world products, and demonstrating the capabilities of latest generation models. We are looking for engineers with a strong track record of building and shipping software, ideally with experience in early-stage environments where they have contributed to scaling products from initial concept to production. The ideal candidate will be motivated by the opportunity to drive product & business impact.

This role requires a strong software engineering foundation and a passion for building and iterating on software products, using state-of-the-art GenAI tools. We are looking for engineers who thrive in fast-paced environments and have a proven ability to deliver high-quality code. Experience in prototyping, building, and scaling software is essential. We particularly value experience in early-stage or startup environments, where engineers take ownership and drive product development from the ground up.

Job responsibilities

• Design and develop scalable software applications leveraging generative AI models.
• Rapidly prototype new features and iterate based on evaluation results.
• Collaborate with researchers and product managers to translate research advancements into tangible product features.
• Optimize software performance and ensure reliability of deployed applications.
• Contribute to the development of best practices for building and deploying generative AI applications.
• Lead the architecture and development of new products & features from 0 to 1.
• A bachelor degree in computer science, electrical engineering or equivalent experience.
• 8 years of experience in software development with one or more programming languages (e.g., Python) and with data structures/algorithms.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, evaluation, data processing, debugging, and fine-tuning), with expertise in areas such as media generation or reinforcement learning.

Preferred qualifications

• Experience with generative AI models and applications.
• Contributions to open-source projects.
• Experience with front end development.
• Experience in rapidly developing and shipping software products in a fast-paced, customer-facing startup-like environment, demonstrating adaptability to changing priorities.
• Experience with cloud computing platforms and infrastructure (e.g., Google Cloud Platform, AWS, Azure).
• Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Hugging Face, etc.