Research Engineer, Gemini Omni Data Infrastructure, DeepMind in London

Research Engineer, Gemini Omni Data Infrastructure, DeepMind in London

London Full-Time 63000 - 77000 £ / year (est.) On-site
Google

At a Glance

  • Tasks: Write and review code, lead design reviews, and debug complex systems.
  • Company: Join DeepMind, a pioneering AI lab transforming global challenges with innovative technology.
  • Benefits: Competitive salary, diverse learning opportunities, and a focus on ethics and safety.
  • Other info: Collaborative environment with varied career pathways for driven individuals.
  • Why this job: Make a real impact in AI development and contribute to groundbreaking research.
  • Qualifications: Bachelor’s degree and 2 years of software development or ML research experience required.

The predicted salary is between 63000 - 77000 £ per year.

  • Write product or system development code.
  • Review code developed by other developers and provide feedback to ensure best practices (e. g., style guidelines, checking code in, accuracy, testability, and efficiency).
  • Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
  • Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
  • Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.

Minimum qualifications

  • Bachelor’s degree or equivalent practical experience.
  • 2 years of software development or ML research experience, or education equivalent credit (e. g., internships, student research, pre-graduate working experience).
  • Experience conducting research to solve problems in AI or ML.
  • Experience in implementing machine learning algorithms or techniques (e. g., basicautomatic differentiation) and in using machine learning frameworks (e. g., Jax, Py Torch, Triton).
  • Experience designing and operating distributed computing systems for large-scale AI/ML workloads.
  • One or more scientific publication submission(s) for conferences, journals, or public repositories, including publications on machine learning or computational neuroscience.

Preferred qualifications

  • Experience with distributed storage systems, relational databases, and schema or query design (e. g., Postgre SQL, Cloud Spanner, Bigtable, Cassandra, or Dynamo DB).
  • Experience with large-scale data pipelines and distributed batch or streaming frameworks (e. g., Apache Beam, Spark, Dataflow, Ray, or Flink).
  • Prior experience building data infrastructure, pipelines, or tooling within an ML research environment.
  • Familiarity with a compiled systems/backend language (such as C++, Rust, Go, or Java) or media codecs (video, audio, image).

Artificial intelligence will be one of humanity’s most transformative inventions.

At Deep Mind, 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 varied learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

  • Bachelor’s degree or equivalent practical experience.
  • 2 years of software development or ML research experience, or education equivalent credit (e. g., internships, student research, pre-graduate working experience).
  • Experience conducting research to solve problems in AI or ML.
  • Experience in implementing machine learning algorithms or techniques (e. g., basicautomatic differentiation) and in using machine learning frameworks (e. g., Jax, Py Torch, Triton).
  • Experience designing and operating distributed computing systems for large-scale AI/ML workloads.
  • One or more scientific publication submission(s) for conferences, journals, or public repositories, including publications on machine learning or computational neuroscience.

Research Engineer, Gemini Omni Data Infrastructure, DeepMind in London employer: Google

As a Senior Manager in Ads Solutions Engineering at gTech, you will thrive in a dynamic and innovative environment that prioritises collaboration and professional growth. The company fosters a culture of continuous learning and development, offering ample opportunities to lead transformative projects while working with cutting-edge technologies. Located in a vibrant tech hub, gTech provides a unique chance to engage with top-tier clients and contribute to impactful solutions that drive success.

Google

Contact Details:

Google Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Research Engineer, Gemini Omni Data Infrastructure, DeepMind in London

✨Join Local Tech Meetups

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We think you need these skills to ace Research Engineer, Gemini Omni Data Infrastructure, DeepMind in London

Software Development
Machine Learning Research
Machine Learning Algorithms
Jax
PyTorch
Triton
Distributed Computing Systems

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Google.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Google and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Google

✨Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

✨Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Google uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

✨Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

✨Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.