Research Scientist, Deep Learning at Deepmind

Research Scientist, Deep Learning – Google DeepMind Location: Mountain View or SFO The Role: Google DeepMind is looking for a Research Scientist to join the Deep Learning organization. This role is designed for a high-impact individual who balances deep theoretical intuition with a "builder" mindset. You will be responsible for advancing the frontier of machine learning by developing novel architectures and scaling training paradigms. You are expected to navigate ambiguity, lead technical workstreams, and bridge the gap between abstract research concepts and robust, executable code. We are looking for a strong hacker—someone who thrives in the codebase and views implementation as a core part of the scientific process. Core Responsibilities • Innovate & Execute: Design, implement, and evaluate complex deep learning models. You won’t just theorize; you will build the prototypes that prove the theory. • Technical Leadership: Act as a primary contributor to large-scale research projects, guiding the technical direction and ensuring code quality and experimental rigor. • Collaborative Building: Work closely with Research Engineers and cross-functional teams to integrate research breakthroughs into scalable infrastructure. • Scientific Contribution: Publish high-quality research at top-tier venues (NeurIPS, ICML, ICLR, etc.) while maintaining a focus on tangible algorithmic improvements. • Mentorship: Provide technical guidance to junior researchers and engineers, fostering a culture of excellence and rapid iteration. Minimum Qualifications • The Fundamentals: A Bachelors or Masters in Computer Science, Mathematics, or a related field, or equivalent practical experience. You must possess an expert-level grasp of the basics of ML (e.g., optimization, linear algebra, statistical learning theory). • Hacker Mentality: Extensive experience with JAX, PyTorch, or TensorFlow. You should be comfortable "getting your hands dirty" in large codebases and debugging complex distributed systems. • Proven Impact: A track record of leading research projects from ideation to deployment or publication. • Builder Portfolio: Evidence of building significant software, tools, or models (e.g., open-source contributions, high-impact internal tools, or large-scale model releases). Preferred Qualifications • Experience with large-scale distributed training and performance profiling. • Ability to translate "blue-sky" research ideas into concrete, incremental engineering milestones. • Strong communication skills with the ability to influence both internal stakeholders and the broader research community. The US base salary range for this full-time position is between $174,000 USD - 252,000 USD + 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.