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 maximise 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.
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.
- Optimise 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.
Requirements:
- 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 optimising 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.