Senior Staff Research Scientist

Google Inc.; Mountain View (CA); On-site; USD 262,000 - 364,000; Full time

Job summary

Google is seeking a Senior Staff Research Scientist to lead foundational research in machine learning, uncertainty quantification, and autonomous systems. You will set long-term research agendas, drive experiments, and collaborate with cross-functional teams to translate breakthroughs into scalable products and infrastructure.

The role emphasizes publishing high-impact work, mentoring teams, and advancing state-of-the-art in computer science across ML, CV, robotics, and data analysis.

Qualifications

• Experience owning outcomes and making decisions in research contexts.
• Proven ability to influence stakeholders and solve ambiguous problems.
• Demonstrated leadership in setting research directions for large teams.

Responsibilities

• Lead research agendas and deploy scalable algorithms.
• Publish findings in top conferences/journals and contribute to open datasets.
• Collaborate with software engineers and product teams to translate research into systems.
• Drive multi-year research programs and set technical direction.

Skills

Outcome ownership

Decision making

Stakeholder influence

Ambiguity solving

Education

Ph.D. in CS/Robotics/EE/Statistics or related field

Tools

JAX

TensorFlow

Job description

corporate_fare Google place Mountain View, CA, USA

Advanced

Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders;deep expertise in domain.

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• Ph.D. in Computer Science, Robotics, Electrical Engineering, Statistics, or a related field (or equivalent practical experience).
• 6 years of experience leading research agendas, developing scalable algorithms, or deploying ML models in production or applied research environments.
  
• Experience with deep learning frameworks (e.g., JAX, TensorFlow) and with distributed training/evaluation pipelines.
  
• One or more scientific publication submission(s) for conferences, journals, or public repositories.(e.g., NeurIPS, ICML, CVPR, ECCV, ICCV, ICRA, CoRL).

Preferred qualifications:

• 6 years of experience leading complex research projects and setting technical direction in autonomous systems or mobile robotics.
• Experience designing, distilling, and optimizing neural architectures for low-latency, real-time edge hardware and onboard compute constraints.
• Proficiency in modern programming languages and working with large-scale distributed training infrastructure.
• Demonstrated track record in deep learning, epistemic/aleatoric uncertainty quantification, model calibration for decision-making, and out of distribution diagnosis and generalization. .
• Strong background in self-supervised learning, multimodal foundation models, latent and embedded spaces, or foundational representations.

About the job

As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.

As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

Google Research drives fundamental breakthroughs, product and large-scale infrastructure and algorithmic advances. In this role, you will work at the frontier of machine learning, statistical inference, learning, and uncertainty quantification. You will guide multi-year research agendas that solve open-ended technical issues, inventing novel technologies and translating them into real-world autonomous systems. You will be actively involved in setting up experiments, demonstrating impact, and integrating and transferring new algorithms and models into products.

Google Research is building the next generation of intelligent systems for all Google products. To achieve this, we’re working on projects that utilize the latest computer science techniques developed by skilled software developers and research scientists. Google Research teams collaborate closely with other teams across Google, maintaining the flexibility and versatility required to adapt new projects and foci that meet the demands of the world's fast-paced business needs.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

About the job

As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.

As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

Google Research drives fundamental breakthroughs, product and large-scale infrastructure and algorithmic advances. In this role, you will work at the frontier of machine learning, statistical inference, learning, and uncertainty quantification. You will guide multi-year research agendas that solve open-ended technical issues, inventing novel technologies and translating them into real-world autonomous systems. You will be actively involved in setting up experiments, demonstrating impact, and integrating and transferring new algorithms and models into products.

Google Research is building the next generation of intelligent systems for all Google products. To achieve this, we’re working on projects that utilize the latest computer science techniques developed by skilled software developers and research scientists. Google Research teams collaborate closely with other teams across Google, maintaining the flexibility and versatility required to adapt new projects and foci that meet the demands of the world's fast-paced business needs.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits
Learn more about benefits at Google .

• Scope, lead, and execute foundational research in learning, uncertainty estimation, and automated system diagnosis to enable adaptive perception and decision-making stacks.
• Develop novel methodologies for out-of-distribution (OOD) detection, active learning with demonstrable impact on behavior and semantics, multimodal retrieval, epistemic/aleatoric uncertainty quantification, and sensor-to-perception-to-action stack calibration.
• Partner with research leads, software engineers, and product teams to integrate breakthroughs into scalable, (and possibly real-time) autonomous infrastructure.
• Author high-impact papers in premier machine learning, computer vision, and robotics venues (e.g., CVPR, ECCV, NeurIPS, ICRA, IROS), contributing code, models, and datasets where applicable.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.