Research Engineer, Code Analysis Engineering London, UK
Research Engineer, Code Analysis Engineering London, UK

Research Engineer, Code Analysis Engineering London, UK

London Full-Time 28800 - 48000 ÂŁ / year (est.) No home office possible
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At a Glance

  • Tasks: Join a dynamic team to develop AI systems for code analysis and generation.
  • Company: Google DeepMind is at the forefront of AI, focusing on public benefit and scientific discovery.
  • Benefits: Enjoy a collaborative environment with opportunities for rapid learning and innovation.
  • Why this job: Be part of groundbreaking research that pushes the boundaries of AI and software engineering.
  • Qualifications: Masters in computer science or related field; experience in ML, Python, and code analysis tools required.
  • Other info: Diversity and inclusion are core values; we welcome applicants from all backgrounds.

The predicted salary is between 28800 - 48000 ÂŁ per year.

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

About Us

We’re a dedicated scientific community, committed to “solving intelligence” and ensuring our technology is used for widespread public benefit.

We’ve built a supportive and inclusive environment where collaboration is encouraged and learning is shared freely. We don’t set limits based on what others think is possible or impossible. We drive ourselves and inspire each other to push boundaries and achieve ambitious goals.

To succeed in this role you will need to be passionate about advancing AI systems that can rigorously analyze correctness, safety, and security properties of code and generate code that satisfies these properties by construction. You\’ll join an energetic team of computer scientists, ML researchers and engineers. You\’ll leverage our unique mix of expertise, data and computational resources to experiment and iterate both rapidly and at scale.

As an embedded Research Engineer you will collaborate with research scientists and software engineers to develop and run experiments, exploring ways to develop AI systems for code analysis and generation. The team is exploring many different foundational and applied challenges in software engineering and security, so you may take part in exploratory work validating early ideas or work in a maturing area to deepen and exploit a promising line of research. You will also contribute to the knowledge and experience of the team with your own knowledge.

Key responsibilities:

  • Plan and perform rapid prototyping of ML-based techniques for automatically analyzing and generating code.
  • Undertake exploratory analysis to inform experimentation and research directions.
  • Make improvements to model architectures and training procedures of machine learning models used for code analysis.
  • Implement tools, libraries and frameworks to speed up and enable new research.
  • Report and present software developments, experimental results and data analysis clearly and efficiently.
  • Collaborate with internal and external domain experts.

The role will suit candidates who enjoy working in a heavily experimental setting with large and noisy datasets and who wish to immerse themselves in innovative science, ML and AI research.

About You

In order to set you up for success as a Research Engineer at Google DeepMind, we look for the following skills and experience:

  • Masters degree in computer science, electrical engineering, mathematics, or equivalent experience.
  • Understanding of foundational principles of code analysis (e.g., invariant generation, abstract interpretation).
  • Experience building tools for code analysis and generation.
  • Experience with Python and preferably Rust and C++.
  • Applied experience with machine learning, preferably modern deep learning techniques (e.g. Transformers, Diffusion Models, LLMs) and reinforcement learning.
  • Experience exploring, analysing and visualising data.
  • Experience using Jax, PyTorch, TensorFlow, NumPy, Pandas or similar ML libraries.

In addition, the following would be an advantage:

  • Experience with formal mathematical reasoning, and in particular, the Lean theorem-prover.
  • Prior experience building AI-based tools for code analysis and generation.
  • Experience working with large and noisy datasets.
  • Experience collaborating across fields.
  • Broad-based knowledge of current trends in computer science.

When assessing technical background we will take a holistic view of the mix of experience with ML, engineering experience, and foundational computer science. We do not expect you to be an expert in all fields simultaneously. However, since the role serves as a bridge between all three, some experience in each is necessary.

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

Applications close on Monday 14th July @ 5pm UK Time.

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Research Engineer, Code Analysis Engineering London, UK employer: DeepMind Technologies Limited

At Google DeepMind, we pride ourselves on being an exceptional employer, fostering a collaborative and inclusive work culture that encourages innovation and continuous learning. Our London-based team of passionate scientists and engineers is dedicated to advancing artificial intelligence for the public good, offering unique opportunities for professional growth and exploration in cutting-edge research. With access to extensive resources and a commitment to ethical practices, we empower our employees to push boundaries and achieve remarkable goals in a supportive environment.
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Contact Detail:

DeepMind Technologies Limited Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Research Engineer, Code Analysis Engineering London, UK

✨Tip Number 1

Familiarise yourself with the latest advancements in AI and machine learning, particularly in code analysis. Follow relevant research papers and attend webinars or conferences to stay updated on trends and innovations in the field.

✨Tip Number 2

Engage with the community by contributing to open-source projects related to code analysis and generation. This not only enhances your skills but also showcases your commitment and expertise to potential employers like us.

✨Tip Number 3

Network with professionals in the AI and software engineering fields. Use platforms like LinkedIn to connect with current employees at Google DeepMind and seek informational interviews to learn more about their work culture and expectations.

✨Tip Number 4

Prepare for technical interviews by practising coding challenges and problems related to machine learning and code analysis. Websites like LeetCode or HackerRank can be great resources to sharpen your problem-solving skills.

We think you need these skills to ace Research Engineer, Code Analysis Engineering London, UK

Machine Learning
Deep Learning Techniques
Code Analysis
Prototyping Skills
Data Analysis and Visualisation
Python Programming
Rust Programming
C++ Programming
Experience with ML Libraries (Jax, PyTorch, TensorFlow, NumPy, Pandas)
Understanding of Invariant Generation
Abstract Interpretation
Collaborative Skills
Exploratory Analysis
Model Architecture Improvement
Formal Mathematical Reasoning
Experience with Large Datasets

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, code analysis, and programming languages like Python, Rust, and C++. Emphasise any projects or roles that demonstrate your ability to work with large datasets and your understanding of foundational principles of code analysis.

Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and how it aligns with the mission of Google DeepMind. Discuss specific experiences that showcase your skills in ML techniques and your collaborative work with engineers and researchers.

Showcase Relevant Projects: Include links to any relevant projects on platforms like GitHub. Highlight your contributions to code analysis tools or AI-based systems, and explain the impact of these projects on your understanding of the field.

Prepare for Technical Questions: Anticipate technical questions related to machine learning, code analysis, and programming. Be ready to discuss your experience with libraries like Jax, PyTorch, and TensorFlow, as well as your approach to problem-solving in experimental settings.

How to prepare for a job interview at DeepMind Technologies Limited

✨Show Your Passion for AI

Make sure to express your enthusiasm for artificial intelligence and its applications. Discuss any personal projects or experiences that demonstrate your commitment to advancing AI systems, especially in code analysis and generation.

✨Demonstrate Technical Knowledge

Be prepared to discuss foundational principles of code analysis, machine learning techniques, and programming languages like Python, Rust, and C++. Highlight any relevant experience you have with tools and libraries such as Jax, PyTorch, or TensorFlow.

✨Prepare for Collaborative Scenarios

Since the role involves working closely with research scientists and software engineers, think of examples where you've successfully collaborated across disciplines. Be ready to discuss how you approach teamwork and share knowledge within a group.

✨Discuss Your Problem-Solving Approach

In an experimental setting, showcasing your analytical skills is crucial. Prepare to talk about how you tackle complex problems, especially when dealing with large and noisy datasets. Share specific instances where your exploratory analysis led to significant insights.

Research Engineer, Code Analysis Engineering London, UK
DeepMind Technologies Limited
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