Job Description
Snapshot
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
Model distillation is a key innovation enabling the acceleration of AI, turning large general models into small and specialized models used across the industry. However, distillation techniques can also be used to steal critical model capabilities, representing a significant threat to the intellectual property and integrity of our foundational models.
The Role
As part of the Security & Privacy Research Team at Google DeepMind, you will build our first line of distillation and security defenses: a state-of-the-art detection system. You will research, design, and train novel classifiers to identify distillation and other security threats in real time. This is a unique opportunity to build the core detection system that protects Gemini. You will be at the forefront of defining how we monitor and protect GDM models by building the core systems that identify sophisticated threats.
Key Responsibilities
+ Build Scalable Classifier Infrastructure: Design and build scalable pipelines for training and evaluating many novel classifiers.
+ Train and Evaluate Classifiers: Train and evaluate classifiers for distillation detection and other key GDM security priorities.
+ Own Classifier Deployment and Integration: Collaborate with model training, infrastructure, and deployment teams to deploy classifiers into our production models.
About You
We are looking for a research scientist, research engineer, or software engineer who is passionate about building the detection systems that protect the future of AI. You are an expert in machine learning, with a deep focus on designing, training, and evaluating classifiers. You thrive on ambiguity and enjoy the challenge of iterating to achieve state-of-the-art detection capabilities.
Minimum qualifications:
+ Ph.D. in Computer Science or a related quantitative field, or a B.S./M.S. in a similar field with 2+ years of relevant industry experience.
+ Demonstrated research or product expertise in machine learning, with a focus on classifier training, classifier evaluation and model evaluation.
Preferred qualifications:
+ Deep expertise in training and evaluating a wide range of classifier architectures.
+ Proven experience building and scaling ML training and evaluation infrastructure.
+ Experience building data pipelines using LLM autoraters.
+ Strong understanding of model distillation, model stealing, and other capability extraction techniques.
+ Strong software engineering skills and experience with ML frameworks like JAX, PyTorch, or TensorFlow.
+ A track record of landing research impact or shipping production ML systems in a multi-team environment.
The US base salary range for this full-time position is between $166,000 - $244,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.
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.
Job Tags
Full time,
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