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Staff Research Engineer, Applied ML

England, United Kingdom (On-site)

Staff Research Engineer, Applied ML

3 Weeks ago • 8-13 Years • Artificial Intelligence

About the job

Summary

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. As a Staff Research Engineer, Applied ML you will be working on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. The Domain Applied ML team is an impactful group within Core ML, dedicated to accelerating the adoption of cutting-edge ML/AI across Google. We bridge the gap between research and production by developing standardized, efficient ML solutions in critical domains like parameter-efficient tuning, multimodal modeling, media generation, LLMs, and recommender systems. You will be building and leading a new team of ML engineers and researchers in London. You will be collaborating with Google Research and DeepMind to identify and prioritize emerging research areas. You will be conducting applied research on emerging ML/AI topics and driving the adoption of new AI technologies across Google products. You will be developing and evaluating ML models for pilot projects and scalable solutions. You will be developing a strategic roadmap for translating research into practical solutions.

9 skills required for this role

Test your skills to join the top 1% applicants for this job

cpp

algorithms

reinforcement-learning

computer-vision

data-structures

python

communication

networking

game-texts

Must have:

Bachelor's degree or equivalent practical experience
8 years of experience in software development and with data structures/algorithms
5 years of experience building and architecting large-scale, production quality Machine Learning (ML) systems
5 years of experience in distributed development and large-scale data processing
Experience coding in either C++ or Python
Experience with ML fundamentals, algorithms, and techniques, including supervised, unsupervised, and reinforcement learning, and experience in areas like natural language processing (NLP), computer vision, and generative AI

Good to have:

Experience with generative models (e.g., diffusion models, GANs, transformers) for various media formats (e.g., text, image, video, audio), including prompt engineering, fine-tuning, and evaluation techniques.
Experience with RL algorithms and frameworks, including policy gradient methods, Q-learning, and actor-critic architectures.
Experience building and leading high-performing research or engineering teams, fostering a positive and inclusive culture.
Experience being published in ML/AI conferences or journals, demonstrating a strong research background and ability to communicate complex technical concepts effectively.
Familiarity with agent-based architectures, tool use, reinforcement learning, and techniques for evaluating and optimizing agent behavior.

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Minimum qualifications:

Bachelor's degree or equivalent practical experience
8 years of experience in software development and with data structures/algorithms.
5 years of experience building and architecting large-scale, production quality Machine Learning (ML) systems.
5 years of experience in distributed development and large-scale data processing.
Experience coding in either C++ or Python.
Experience with ML fundamentals, algorithms, and techniques, including supervised, unsupervised, and reinforcement learning, and experience in areas like natural language processing (NLP), computer vision, and generative AI.

Preferred qualifications:

Experience with generative models (e.g., diffusion models, GANs, transformers) for various media formats (e.g., text, image, video, audio), including prompt engineering, fine-tuning, and evaluation techniques.
Experience with RL algorithms and frameworks, including policy gradient methods, Q-learning, and actor-critic architectures.
Experience building and leading high-performing research or engineering teams, fostering a positive and inclusive culture.
Experience being published in ML/AI conferences or journals, demonstrating a strong research background and ability to communicate complex technical concepts effectively.
Familiarity with agent-based architectures, tool use, reinforcement learning, and techniques for evaluating and optimizing agent behavior.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

The Domain Applied ML team is an impactful group within Core ML, dedicated to accelerating the adoption of cutting-edge ML/AI across Google. We bridge the gap between research and production by developing standardized, efficient ML solutions in critical domains like parameter-efficient tuning, multimodal modeling, media generation, LLMs, and recommender systems.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Responsibilities

Build and lead a new team of ML engineers and researchers in London.
Collaborate with Google Research and DeepMind to identify and prioritize emerging research areas.
Conduct applied research on emerging ML/AI topics and drive the adoption of new AI technologies across Google products.
Develop and evaluate ML models for pilot projects and scalable solutions.
Develop a strategic roadmap for translating research into practical solutions.

View Full Job Description

About The Company

Google

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A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.