Staff Software Engineer, Medical AI, Google DeepMind

Google Inc.; Singapore; On-site; SGD 100,000 - 130,000; Full time

Job summary

A leading tech company based in Singapore is seeking a Staff Software Engineer to design and implement innovative AI systems for healthcare. The role requires extensive experience in software development, proficiency in C++ and Python, and collaboration abilities within a fast-paced environment. Ideal candidates will have a bachelor's degree in Computer Science or a related field and a strong background in full-stack web development. This position offers the chance to work on cutting-edge projects that aim to transform human health.

Qualifications

• Minimum 7 years of software development experience.
• Proven experience in full stack web development.
• Strong background in scalable systems design.

Responsibilities

• Design and implement AI systems in medicine.
• Collaborate with engineers to ensure system safety.
• Contribute to cutting-edge medical AI systems.

Skills

C++

Python

Full stack development

Agile methodologies

Collaboration

Education

Bachelor's degree in Computer Science or equivalent

Tools

Angular

Typescript

Job description

Job Description

Our interdisciplinary team combines the best techniques from deep learning, reinforcement learning and systems neuroscience to build general-purpose learning algorithms and apply these to medicine and healthcare. We have already made a number of high profile breakthroughs towards building artificial general intelligence for medicine.

In this role, you will accelerate development and deployment of multimodal and multi-agent conversational AI systems. You’ll work with a global group of engineers and research scientists on a mission-driven team, with high agency in a fast-paced environment. Together, you will build and deploy cutting-edge medical AI systems for real-world healthcare with rigorous and careful evaluation, while respecting all aspects of domain-specific compliance.

Job Responsibilities

• Design, develop and implement highly scalable, secure, and performant systems for AI in medicine and health or other high-compliance requirement safety-critical systems
• Use your agile and adaptable skill-set to work across timezones and deliver full-stack implementation, from front-end, back-end, to the agentic AI system
• Apply your software engineering expertise to produce high quality, clean, generalisable/reusable and scalable code and infrastructure
• Collaborate with researchers and engineers in the team to ensure system safety and reliability
• Be highly collaborative, striving to cultivate a culture of continuous development and advancement.
• Implement tools, libraries and frameworks, and build on existing systems, to accelerate and enable new research and deployments.
• Employ cutting-edge technology and techniques to contribute to solving some of the hardest problems.
• Incorporate your passion for advancing human health and any previous knowledge or academic experience to join a team of hardworking individuals who openly collaborate with one another.

Minimum qualifications

Software Engineers come from a diverse set of backgrounds, sometimes with degrees in Computer Science and sometimes with extensive experience with real problems, or both.

In order to set you up for success as a Staff Software Engineer at Google DeepMind, we look for the following skills and experience:

• A bachelor degree in computer science, electrical engineering or equivalent experience
• 7+ years of experience with software development using programing language such as C++ and Python
• 7+ years of experience in full stack web development using Angular and/or Typescript

Preferred qualifications

• 2+ years experience developing and deploying an end-to-end LLM-powered system, and/or multi-agent and multimodal models including audio and video
• Experience optimising large-scale training and fine-tuning large models.
• Experience with compliant enterprise product development and data management in production
• Experience with multimodal LLM and multi-agent systems and evaluation