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Google Research Scientist Jobs (NOW HIRING)

MongoDB

Staff Research Scientist

Palo Alto, CA · On-site +1

Position Overview We are seeking a Staff Research Scientist to join our team and contribute to the ... Google Cloud, and Microsoft Azure. With offices worldwide and over 67,000 customers, including 75 ...

MongoDB

Senior Research Scientist

Palo Alto, CA

$115K - $147K/yr

Position Overview We are seeking a Senior Research Scientist to join our team and contribute to the ... Google Cloud, and Microsoft Azure. With offices worldwide and over 67,000 customers, including 75 ...

MongoDB

Staff Research Scientist

Palo Alto, CA · On-site

  • Medical

  • Retirement

  • PTO

Position Overview We are seeking a Staff Research Scientist to join our team and contribute to the ... Google Cloud, and Microsoft Azure. With offices worldwide and over 67,000 customers, including 75 ...

P-1 AI

AI Research Scientist

San Francisco, CA · On-site

$200K - $385K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... Google and OpenAI. About the opportunity: We're seeking an exceptional AI Research Scientist to ... join our small team of elite researchers and help us push the boundaries of AI applied to the ...

MongoDB

Senior Research Scientist

Palo Alto, CA · On-site

$126K - $248K/yr

  • Medical

  • Retirement

  • PTO

Position Overview We are seeking a Senior Research Scientist to join our team and contribute to the ... Google Cloud, and Microsoft Azure. With offices worldwide and over 67,000 customers, including 75 ...

Chewy

Research Scientist III

Bellevue, WA

$148K - $225K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Chewy's Supply Chain is seeking a Research Scientist III of a balanced background in optimization ... AWS, Azure, Google cloud, etc. * 3+ years industry experience on solving business problem in ...

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All JobsGoogle Research Scientist Jobs

Google Research Scientist information

See salary details

$50.5K

$130.1K

$174K

How much do google research scientist jobs pay per year?

As of Aug 15, 2026, the average yearly pay for google research scientist in the United States is $130,117.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,500.00 and $173,000.00 per year, depending on experience, location, and employer.

How to become a Google research scientist?

To become a Google research scientist, candidates typically need a strong educational background in computer science, engineering, or related fields, often with a Ph.D. or equivalent experience in areas like machine learning, artificial intelligence, or data science. Relevant skills include programming in languages such as Python or C++, experience with research methodologies, and a track record of published research or contributions to open-source projects. Building a strong portfolio of research work and gaining experience through internships or academic collaborations can also improve chances of selection.

What does a Google Research Scientist do?

A Google Research Scientist conducts cutting-edge research to develop new technologies and advance the state of the art in fields such as artificial intelligence, machine learning, natural language processing, and computer vision. They work on both theoretical and applied projects, often collaborating with other researchers and product teams to solve complex problems. Their contributions can lead to innovative features in Google products and may also be published in leading scientific conferences and journals.

How does a Google Research Scientist typically collaborate with cross-functional teams within the company?

As a Google Research Scientist, you can expect to work closely with cross-functional teams, including engineers, product managers, and data analysts. Collaboration often involves sharing research findings, integrating new algorithms into products, and iterating on prototypes based on feedback from other teams. Regular meetings, code reviews, and joint project planning sessions are common, ensuring that research outcomes are aligned with product goals and user needs. This collaborative environment not only accelerates innovation but also provides valuable exposure to diverse perspectives and skill sets.

What is the difference between Google Research Scientist vs Google Data Scientist?

AspectGoogle Research ScientistGoogle Data Scientist
Required CredentialsAdvanced degrees in CS, AI, or related fields; strong research backgroundDegree in CS, Statistics, or related; strong analytical skills
Work EnvironmentFocus on research, developing new algorithms, publishing papersFocus on data analysis, building models, supporting product decisions
Employer & Industry UsagePrimarily in research labs, AI teams, academia collaborationsAcross product teams, marketing, and analytics departments

Google Research Scientists primarily focus on advancing AI and machine learning through research and publications, while Google Data Scientists analyze data to inform product decisions and improve user experience. Both roles require strong technical skills, but differ in their core objectives and work environment.

What are the key skills and qualifications needed to thrive as a Google Research Scientist?

To thrive as a Google Research Scientist, a strong background in computer science, mathematics, and research methodology—typically demonstrated by a PhD or equivalent experience—is essential. Proficiency in programming languages like Python or C++, machine learning frameworks (such as TensorFlow or PyTorch), and experience with large-scale data systems are commonly required. Outstanding problem-solving, collaboration, and communication skills set top candidates apart in this role. These capabilities are crucial for driving innovative research, publishing impactful work, and contributing to multidisciplinary team projects at Google.
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Google Research Scientist jobs near you
Infographic showing various Google Research Scientist job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 87% Full Time, 9% Part Time, and 2% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $130,117 per year, or $62.6 per hour.

Machine Learning Research Scientist

Autoscience

Menlo Park, CA • On-site

Full-time

PTO

Re-posted 4 days ago

Job description

Company Description

At Autoscience Institute, we create AI systems that autonomously conduct AI research. Recently, we announced the first AI agent to autonomously create peer-reviewed literature (ICLR 2025 Workshops). We are passionate about pushing the boundaries of artificial intelligence and contributing to groundbreaking advancements in the field.

Role Description

This is a full-time on-site role for a Machine Learning Research Scientist located in the San Francisco Bay Area.

  • Work directly with the founder to develop autonomous research systems that ideate, experiment, and improve customer models.

  • Collaborate with the engineering team to build and deploy production-ready research systems.

  • RL post-train and fine-tune reasoning models to automate components of the machine learning research process.

  • Stay current with the latest developments in AI research and automation.

Qualifications:

  • Education: PhD or equivalent research experience in Computer Science, Machine Learning, Artificial Intelligence, or a related field. Exceptional candidates with strong research contributions are encouraged to apply regardless of formal degree.

  • Research: Publishing in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR, etc) or equivalent industry experience at corporate AI research labs (Microsoft, Google, Nvidia, TRI etc).

  • Technical: Expertise in training machine learning models, including deep learning, reinforcement learning or genetic algorithms. This does not include building multi-agent systems using LLM APIs or building RAG-based agents.

  • Curiosity: Passion for accelerating scientific discovery through AI and willingness to explore uncharted directions with minimal supervision.

Recommended Qualifications

  • Systems: Experience building scalable and production-ready machine learning pipelines or large-scale model training (distributed model training over >64 GPUs).

  • Science: Any background or proven interested in Automated Scientific Research is a plus.

Benefits & Perks

  • Our comp is competitive against major LLM frontier lab packages

  • Unlimited PTO and flexible working arrangements

  • Conference attendance and publication support

Our Culture

We're a team of passionate researchers and engineers working to automate scientific discovery. We believe in the power of AI to accelerate scientific discovery and are committed to responsible AI development
We are an e-verify employer.