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- Tasks: Lead a team in developing cutting-edge ML solutions and conduct applied research.
- Company: Join Google, a leader in technology, shaping how billions connect and interact.
- Benefits: Enjoy flexible work options, competitive salary, and access to innovative projects.
- Why this job: Be part of a dynamic team driving AI advancements with real-world impact.
- Qualifications: Bachelor's degree, 8 years in software development, and expertise in ML systems required.
- Other info: Opportunity to collaborate with top researchers and switch teams as you grow.
The predicted salary is between 43200 - 72000 £ per year.
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
Staff Research Engineer, Applied ML employer: Google
Contact Detail:
Google Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Research Engineer, Applied ML
✨Tip Number 1
Familiarise yourself with the latest trends in machine learning and AI, especially in areas like generative models and reinforcement learning. This knowledge will not only help you during interviews but also demonstrate your passion for the field.
✨Tip Number 2
Network with professionals in the ML community, particularly those who work at Google or similar companies. Attend conferences, webinars, or local meetups to make connections that could lead to referrals or insider information about the role.
✨Tip Number 3
Showcase your leadership skills by discussing any experience you have in building or leading teams. Prepare examples of how you've fostered a positive culture and driven projects to success, as this is a key aspect of the role.
✨Tip Number 4
Be ready to discuss your experience with large-scale ML systems and distributed development. Prepare specific examples of projects you've worked on, focusing on the challenges you faced and how you overcame them, as this will be crucial in demonstrating your expertise.
We think you need these skills to ace Staff Research Engineer, Applied ML
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in software development, data structures, and algorithms. Emphasise your work with large-scale ML systems and any relevant projects that showcase your skills in C or Python.
Craft a Strong Cover Letter: In your cover letter, explain why you're passionate about applied machine learning and how your background aligns with the responsibilities of the role. Mention specific experiences that demonstrate your leadership abilities and your familiarity with generative models and reinforcement learning.
Showcase Your Research Experience: If you have published work in ML/AI conferences or journals, make sure to include this in your application. Highlight your ability to communicate complex technical concepts effectively, as this is crucial for the role.
Prepare for Technical Questions: Anticipate technical questions related to ML fundamentals, algorithms, and techniques. Be ready to discuss your experience with distributed development and large-scale data processing, as well as your understanding of agent-based architectures and evaluation techniques.
How to prepare for a job interview at Google
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with data structures, algorithms, and large-scale ML systems. Highlight specific projects where you've implemented these skills, especially in C or Python, as this will demonstrate your technical proficiency.
✨Demonstrate Leadership Qualities
Since the role involves building and leading a team, share examples of how you've successfully led teams in the past. Discuss your approach to fostering an inclusive culture and how you motivate team members to achieve their best work.
✨Discuss Your Research Background
If you have publications in ML/AI conferences or journals, be ready to talk about them. Explain complex concepts in a way that shows your ability to communicate effectively, which is crucial for collaboration with research teams.
✨Prepare for Problem-Solving Questions
Expect to tackle questions related to real-world ML challenges. Practice explaining your thought process when approaching problems, particularly in areas like reinforcement learning and generative models, as this will showcase your analytical skills.
