At a Glance
- Tasks: Tackle real-world problems using advanced machine learning and collaborate with diverse teams.
- Company: Join DeepMind, a leader in AI innovation within Google/Alphabet.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on collaboration and innovation.
- Why this job: Make a tangible impact on cutting-edge projects like MuZero for Video Compression.
- Qualifications: Degree in computer science or related field; experience in Python or C++ and machine learning.
The predicted salary is between 70000 - 90000 £ per year.
About the Role
The Applied team at DeepMind works closely with various Google/Alphabet teams, utilizing DeepMind's expertise to deploy advanced machine learning algorithms to enhance Alphabet products and services. This team is driven, collaborative, and diverse, with members based in London and Mountain View. Current and past collaborations include teams in Cloud, Android, Assistant, YouTube, and Maps. The team also collaborates closely with DeepMind's and Google's Research teams on several projects. Each project typically involves a team of engineers working with product partners, researchers, product managers, and program managers.
Key Responsibilities
- Apply the most promising models and research to high-impact real-world problems.
- Rapid-prototype initial concepts.
- Design and run experiments to evaluate opportunities.
- Gain an understanding of the path from research to production while working on real-world problems.
- Work as part of a small project team led by Research Engineers, with potential for partnership with research scientists.
Current projects, such as MuZero for Video Compression, focus on areas including Natural Language Generation/Understanding, Multimodal Understanding, Reinforcement Learning, Causal/Counterfactual modelling, Time Series Forecasting, Meta Learning, and Multitask Learning. Experience in any of these areas is highly beneficial.
Requirements
- BSc, MSc or PhD/DPhil degree in computer science, mathematics, applied stats, machine learning or similar experience working in industry.
- Proven knowledge and experience of Python or C++.
- Knowledge of machine learning and statistics.
- Knowledge of algorithm design.
- Proven experience of TensorFlow or similar ML frameworks (e.g. JAX) is highly desirable.
- Software Engineering experience and experience working on large-scale ML projects highly desirable.
- Proven experience working in industry, on projects from proof-of-concept through to implementation highly beneficial.
- A passion for AI.
- Great communication skills and proven interpersonal skills.
Additional Advantages
- Experience in applying experimental ideas to applied problems.
- Cross‑functional collaboration experience.
- Prior experience collaborating with researchers.
- Prior experience working with product teams.
Senior Research Engineer, Applied employer: Google DeepMind
DeepMind is an exceptional employer, offering a dynamic and collaborative work culture that thrives on innovation and diversity. Located in London, the Applied team provides unique opportunities for professional growth through hands-on experience with cutting-edge machine learning projects, while fostering cross-functional collaboration with various Google/Alphabet teams. Employees benefit from a supportive environment that encourages creativity and adaptability, making it an ideal place for those passionate about AI and looking to make a meaningful impact.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Research Engineer, Applied
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at DeepMind or similar companies. Use LinkedIn to connect and engage with them; you never know who might help you land that interview.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning and Python or C++. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your algorithm design and machine learning concepts. Practice coding challenges and be ready to discuss your past projects in detail—this is where you can really shine!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining us at StudySmarter. Tailor your application to highlight how your experience aligns with the role and our mission.
We think you need these skills to ace Senior Research Engineer, Applied
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Senior Research Engineer role. Highlight your experience in machine learning, Python or C++, and any relevant projects you've worked on. We want to see how you can contribute to our team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a great fit for the Applied team. Be sure to mention any collaborative projects you've been part of, as teamwork is key for us.
Showcase Your Projects:If you've worked on any interesting projects, especially those involving machine learning or algorithm design, make sure to include them in your application. We love seeing real-world applications of your skills, so don't hold back!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you'll find all the details you need about the role and our team there!
How to prepare for a job interview at Google DeepMind
✨Know Your Stuff
Make sure you brush up on your knowledge of machine learning algorithms and frameworks like TensorFlow or JAX. Be ready to discuss how you've applied these in real-world projects, as this will show your practical experience and understanding of the field.
✨Show Your Flexibility
This role requires adaptability, so be prepared to share examples of how you've navigated ambiguity in past projects. Highlight situations where you had to pivot your approach or invent novel solutions to overcome challenges.
✨Collaborate Like a Pro
Since the team works closely with various product partners and researchers, emphasise your experience in cross-functional collaboration. Share specific instances where teamwork led to successful outcomes, showcasing your communication skills and ability to work well with others.
✨Experiment and Evaluate
Discuss your experience with designing and running experiments to evaluate opportunities. Be ready to talk about how you approach rapid prototyping and what metrics you use to assess the success of your projects, as this aligns perfectly with the key responsibilities of the role.
