Senior Applied AI Engineer

Google DeepMind; London; On-site; GBP 90,000 - 120,000; Full time

Job summary

A leading AI research organization in London is seeking a Senior Applied AI Engineer to enhance its generative AI models. Candidates should have extensive experience in software development and a strong background in AI research. The ideal applicant thrives in fast-paced environments and has a passion for building cutting-edge software solutions. This role offers the opportunity to drive substantial product impact within the team.

Qualifications

• 8 years of experience in software development.
• 5 years of hands-on experience in AI research, applications, or model deployment.
• Proven ability to rapidly develop and ship software products.
• Deep understanding of software development best practices.

Responsibilities

• Drive real-world high-impact outcomes using frontier models.
• Build evaluations, training data, and infrastructure for AI deployments.
• Collaborate with researchers and product managers to translate research advancements.
• Develop best practices for building generative AI applications.
• Lead architecture and development of new products and features.

Skills

Software development

Data structures/algorithms

AI research

AI applications

Model deployment

Cloud computing

Machine learning frameworks

Adaptability

Education

Bachelor's degree or equivalent practical experience

Tools

TensorFlow

PyTorch

Hugging Face

Google Cloud Platform

AWS

Azure

Job description

We are seeking a Senior 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 AI-powered 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.

About us

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

The role

This role requires a strong machine learning foundation and a passion for building and iterating on software products. We are looking for machine learning 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.

Key responsibilities

• Harness frontier models to drive real-world high-impact outcomes
• Build evaluations, training data, and infrastructure to support AI deployments and rapid iterations
• Collaborate with researchers and product managers to translate research advancements into tangible product features.
• Contribute to the development of best practices for building and deploying generative AI applications.
• Contribute signal to influence the development of frontier models
• Lead the architecture and development of new products & features from 0 to 1.

About you

In order to set you up for success as an Applied AI Engineer at Google DeepMind, we look for the following skills and experience:

Required Skills

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development, and with data structures/algorithms.
• 5 years of hands-on experience in AI research (e.g. RL, finetuning, evals), AI applications, or model deployment
• Proven experience in rapidly developing and shipping software products.
• Deep understanding of software development best practices, including testing & deployment.
• Experience with cloud computing platforms and infrastructure (e.g., Google Cloud Platform, AWS, Azure).
• Substantial experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Hugging Face, etc.
• Ability to work in a fast-paced environment and adapt to changing priorities.

Preferred Skills

• Experience with generative AI research or applications.
• Contributions to open-source projects.
• Experience working in, or founding early stage startups.
• Experience delivering software solutions in a fast-paced, customer-facing environment.

If you are a passionate machine learning engineer with a drive to build innovative products and a desire to work at the forefront of AI, we encourage you to apply!

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

Create a Job Alert

Interested in building your career at DeepMind? Get future opportunities sent straight to your email.

Apply for this job

*

indicates a required field

First Name *

Last Name *

Email *

Phone

Resume/CV *

Enter manually

Accepted file types: pdf, doc, docx, txt, rtf

Enter manually

Accepted file types: pdf, doc, docx, txt, rtf

LinkedIn Profile

Link to external profile e.g. LinkedIn, GitHub etc.