Research Engineer, Foundational Research, New York
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.
Snapshot
Our team at Google DeepMind focusses on pushing the boundaries of Machine Learning and Artificial Intelligence theory & practice. We work on foundational research which includes but is not limited to deep neural network models, reinforcement learning algorithms and biologically-inspired models with the overall goal of building powerful general-purpose learning algorithms. We work alongside scientists and engineers from other parts of the organisation.
We have created a passionate and engaging culture, combining research and engineering environments, to provide a supportive balance of structure and flexibility. Our approach encourages collaboration across research groups, leading to ambitious creativity and the scope for innovative research breakthroughs.
About us
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.
The role
We are looking for Research Engineers to join a new Research Engineering team in NYC that focuses on accelerating foundational research around large language models, reinforcement learning, and new capabilities for AI agents. . The team will partner with the Gemini team, the research teams and the Research Engineering global teams from experimental research, to tackling large scale engineering challenges, to translating research into applications and products.
As a Research Engineer you will work directly on a wide range of research projects, in collaboration with Research Scientists and Software Engineers. You will apply your engineering and research skills to accelerate research progress through developing prototypes, scaling up algorithms, overcoming technical obstacles, and designing, running, and analysing experiments.
Working in an environment that fosters learning and development, over time you'll start contributing to longer-term and larger-scale initiatives. You'll continue to deepen and broaden your knowledge on a range of research and engineering topics.
Job responsibilities include:
- Working out how to make research methods run with large scale compute.
- Performance engineering, benchmarking, and optimization.
- Solving key research challenges, via designing and running experiments, sharing analyses and proposing next steps.
- Bringing engineering expertise into research projects. Sharing your skills and knowledge with other engineers and researchers.
- Designing, building, and improving infrastructure for 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:
- Bachelor's degree in a technical subject (e.g. machine learning, AI, computer science, mathematics, physics, statistics), or equivalent experience.
- Ability to write code fluently in at least one programming language, preferably Python or C++.
- Knowledge of mathematics, statistics and machine learning concepts needed to understand research papers and processes in the field.
- Ability to communicate technical ideas effectively, e.g. through discussions, whiteboard sessions, written documentation
- Deep understanding of engineering in research.
- Agile mindset
In addition, the following would be an advantage:
- Project management experience
- Experience and deep understanding of multi-accelerator multi-host distributed computation.
- Knowledge of ML/scientific libraries such as TensorFlow, JAX, PyTorch, NumPy and Pandas.
- Machine learning and research experience in industry, academia and personal projects, whether in computer science or other fields such as physics, computational biology, or mathematics.
- Experience with large scale system design.
The US base salary range for this full-time position is between $136,000 - $300,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.
We are also open to relocating candidates to New York, NY and offer a bespoke service and immigration support to make it as easy as possible (depending on eligibility).
Application deadline: 12pm EST Friday 21st June 2024