Staff Research Engineer, Applied ML

Google Inc.; London; On-site; GBP 80,000 - 150,000; Full time

Job summary

An established industry player is seeking a talented Software Engineer to join their innovative team in London. This role involves leading a new group of Machine Learning engineers and researchers, collaborating with top-tier research organizations, and conducting impactful applied research. You will be at the forefront of developing cutting-edge ML solutions that bridge the gap between research and production, enhancing products used by billions globally. If you are passionate about shaping the future of AI technologies and thrive in a dynamic environment, this is the perfect opportunity for you to make a significant impact.

Qualifications

• 8+ years of software development experience with a focus on ML systems.
• Strong background in data structures, algorithms, and large-scale data processing.

Responsibilities

• Lead a new team of ML engineers and researchers in London.
• Conduct applied research on ML/AI topics and drive technology adoption.

Skills

Software Development

Machine Learning

Data Structures

Algorithms

C++

Python

Natural Language Processing

Computer Vision

Generative AI

Education

Bachelor's Degree

Tools

TensorFlow

PyTorch

Job description

Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain.

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.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

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.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law.

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.