Research Engineer, Foundational Research, New York

Join Google DeepMind as a Research Engineer in NYC

At Google DeepMind, we cherish the diversity of experience, knowledge, backgrounds, and perspectives, harnessing 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 conditions (including breastfeeding), or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please let us know.

Snapshot of Google DeepMind

Our team at Google DeepMind is dedicated to advancing the boundaries of Machine Learning and Artificial Intelligence theory and practice. We focus on pioneering research areas including deep neural network models, reinforcement learning algorithms, and biologically-inspired models with the mission of developing powerful general-purpose learning algorithms. Collaboration with scientists and engineers from other parts of our organization is key to our success.

We proudly foster a passionate, engaging culture that merges research and engineering environments to provide a supportive balance of structure and flexibility. Our collaborative approach unlocks ambitious creativity and paves the way for innovative research breakthroughs.

About Us

Artificial Intelligence could be one of humanity’s most transformative inventions. At Google DeepMind, we are a team of scientists, engineers, machine learning experts, and more, united in advancing the state of the art in AI. Our technologies serve public benefit and scientific discovery, and we partner with others on critical challenges, ensuring that safety and ethics remain our highest priorities.

Role Overview: Research Engineer, Foundational Research

We are seeking talented Research Engineers to join our new Research Engineering team in NYC. This team focuses on accelerating foundational research on large language models, reinforcement learning, and new capabilities for AI agents. You will collaborate with the Gemini team, research teams, and global Research Engineering teams, driving both experimental research and large-scale engineering challenges while translating research into applications and products.

As a Research Engineer, you will engage in a wide range of research projects, working directly with Research Scientists and Software Engineers. You'll use your engineering and research skills to develop prototypes, scale up algorithms, overcome technical challenges, and design, run, and analyze experiments. With a commitment to fostering learning and development, you will contribute to longer-term and larger-scale initiatives, continually deepening your knowledge in a range of research and engineering topics.

Job Responsibilities

• Optimizing research methods for large-scale compute.
• Performance engineering, benchmarking, and optimization.
• Designing and executing experiments to solve key research challenges, and proposing next steps based on analyses.
• Bringing engineering expertise to research projects and sharing knowledge with other engineers and researchers.
• Designing, building, and improving research infrastructure.

About You

To excel as a Research Engineer at Google DeepMind, you should have:

• Bachelor's degree in a technical subject (e.g., machine learning, AI, computer science, mathematics, physics, statistics), or equivalent experience.
• Fluency in at least one programming language, preferably Python or C++.
• Knowledge of mathematics, statistics, and machine learning concepts necessary for understanding research papers and processes in the field.
• Ability to communicate technical ideas effectively through discussions, whiteboard sessions, and written documentation.
• A deep understanding of engineering in research.
• An agile mindset.

The following qualifications would be advantageous:

• 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.
• Experience in machine learning and research in industry, academia, or through personal projects in disciplines 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, plus bonus, equity, and benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process. We also offer relocation support to New York, NY, including a bespoke service and immigration support (depending on eligibility).

Application