Research Engineer, Frontier AI, Incubation, DeepMind

MINIMUM QUALIFICATIONS:

* Bachelor's degree in Computer Science, Machine Learning, Mathematics,

Statistics, a related technical field, or equivalent practical experience.

* Experience programming in Python or C++.

* Experience with machine learning, algorithm design, data structures, and

distributed software systems.

* Experience taking technical projects or machine learning systems from

conceptual formulation to implementation and deployment.

PREFERRED QUALIFICATIONS:

* Experience developing, fine-tuning, or optimizing foundation models including

techniques such as RLHF/RLAIF, supervised fine-tuning, parameter-efficient

tuning, or inference optimization.

* Experience with personalization, adaptive systems, user modeling,

retrieval-augmented generation, or agentic memory architectures.

* Experience with modern machine learning frameworks and model training or

serving infrastructure.

* Experience collaborating across research and product boundaries to co-design

technical architectures.

ABOUT THE JOB:

At Google, research-focused Software Engineers are embedded throughout the

company, allowing them to setup large-scale tests and deploy promising ideas

quickly and broadly. Ideas may come from internal projects as well as from

collaborations with research programs at partner universities and technical

institutes all over the world.

From creating experiments and prototyping implementations to designing new

architectures, engineers work on real-world problems including artificial

intelligence, data mining, natural language processing, hardware and software

performance analysis, improving compilers for mobile platforms, as well as core

search and much more. But you stay connected to your research roots as an active

contributor to the wider research community by partnering with universities and

publishing papers.

Artificial intelligence will be one of humanity’s most transformative

inventions. At Google DeepMind, we are a pioneering AI lab with exceptional

interdisciplinary teams focused on advancing AI development to solve complex

global challenges and accelerate high-quality product innovation for billions of

users. We use our technologies for widespread public benefit and scientific

discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer

diverse learning opportunities and varied career pathways for those driven to

achieve exceptional results through collective effort.Individual pay is

determined by factors including job-related skills, experience, and relevant

education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google

[https://www.google.com/about/careers/applications/benefits/].

RESPONSIBILITIES:

* Design, train, and optimize foundational algorithms and machine learning

systems (e.g., personalized model adaptation, agentic workflows, contextual

memory architectures, dynamic prompt optimization, and multimodal reasoning).

* Lead end-to-end technical development from algorithmic design and

experimental prototyping to production-grade architecture and scaled serving

infrastructure.

* Partner directly with engineering and product teams to integrate and harden

core technologies within production environments (e.g., Project Helix, agent

workspaces, and intelligent system integrations).

* Formulate novel automated and human-in-the-loop evaluation methodologies to

measure capability gains, latency/compute efficiency, alignment, and

personalization fidelity.