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Google Colab Jobs (NOW HIRING)

CoLab Software

Senior 3D & AI Systems Software Developer

$125K - $165K/yr

About CoLab At CoLab, we help mechanical engineering teams bring life-changing products to market ... Google Gemini) * Knowledge of ML frameworks such as PyTorch, Hugging Face, or Scikit-learn

Weekday AI

STEM Researcher - Computational Fields

$60 - $90/hr

Working knowledge of Git , integrated development environments (IDEs), and notebook platforms such as Jupyter or Google Colab . * Experience with AI evaluation, benchmark development, AI training, or ...

Owens & Minor, Inc.

Data Scientist

$110K - $117K/yr

... Google Colab for data modeling, processing, and automation. • Design and maintain data warehouse solutions to support advanced analytics and business intelligence. • Perform complex data ...

Owens & Minor

Data Scientist

$110K - $117K/yr

Utilize Palantir Foundry, Google Cloud, AutoAI, and Google Colab for data modeling, processing, and automation. Design and maintain data warehouse solutions to support advanced analytics and business ...

IonQ

Quantum Success Engineer

Hands-on experience with Python and Jupyter Notebook, Google Colab, or similar platforms * Demonstrated experience communicating technical concepts to business stakeholders and technical subject ...

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$24K

$77.7K

$172.5K

How much do google colab jobs pay per year?

As of Sep 14, 2026, the average yearly pay for google colab in the United States is $77,698.00, according to ZipRecruiter salary data. Most workers in this role earn between $34,500.00 and $112,500.00 per year, depending on experience, location, and employer.

What is Google Colab?

Google Colab, short for Google Colaboratory, is a free cloud-based platform that allows users to write and execute Python code through a web browser. It is especially popular for machine learning, data analysis, and education because it provides free access to GPUs and TPUs. Colab notebooks are similar to Jupyter notebooks and support easy sharing and collaboration. Users can also import data from Google Drive and other sources, making it a convenient tool for both beginners and professionals.

What is a Google Colab job?

A Google Colab job typically refers to tasks or projects performed using Google Colaboratory, a cloud-based Jupyter notebook environment. It is commonly used for machine learning, data analysis, and Python development without requiring local setup. Professionals working with Google Colab may include data scientists, AI researchers, and engineers leveraging GPU and TPU resources for computation.

What are some common challenges faced when working as a Google Colab specialist in a collaborative team environment?

As a Google Colab specialist, one common challenge is ensuring smooth collaboration when multiple team members are working on the same notebook, as version control can be tricky. Managing dependencies and ensuring consistent environments across users also requires careful setup, since Colab sessions can reset and lose installed packages. Additionally, dealing with Colab's resource limitations, such as session timeouts or GPU availability, can impact project timelines. Clear communication and structured workflows help mitigate these challenges and support efficient teamwork.

What are the key skills and qualifications needed to thrive as a Google Colab data scientist, and why are they important?

To thrive as a Google Colab Data Scientist, you need a strong foundation in Python programming, data analysis, and machine learning, typically supported by a degree in computer science or a related field. Familiarity with Google Colab, Jupyter Notebooks, TensorFlow, and data visualization libraries is essential. Strong problem-solving, communication, and collaboration skills help you effectively interpret data and share results with stakeholders. These skills enable efficient development and sharing of reproducible data science workflows in a collaborative, cloud-based environment.

What is the difference between Google Colab vs Data Scientist?

FeatureGoogle ColabData Scientist
Primary UseCloud-based platform for coding, collaboration, and machine learning experimentsAnalyzing data, building models, and deriving insights from data
Required SkillsPython, Jupyter notebooks, basic ML knowledgeStatistics, programming, data analysis, ML expertise
Work EnvironmentOnline, collaborative, flexibleOffice or remote, analytical and research-focused
CredentialsNone required, but programming skills neededDegree in data science, statistics, or related field

Google Colab is a tool used by data scientists for coding and experimentation, while a data scientist is a professional who analyzes data and builds models. Google Colab supports data science tasks but is not a job role itself. Understanding the differences helps in choosing the right tools and career path.

How do I get into Google Colab?

Google Colab is a cloud-based platform that allows users to run Python code in Jupyter notebooks. To access it, sign in with a Google account, navigate to colab.research.google.com, and create a new notebook or open existing ones. Basic knowledge of Python and familiarity with Jupyter notebooks are helpful for using Colab effectively.
More about Google Colab jobs

What are the most commonly searched types of Google Colab jobs?

The most popular types of Google Colab jobs are:

What job categories do people searching Google Colab jobs look for?

The top searched job categories for Google Colab jobs are:

Google Colab jobs near you
Infographic showing various Google Colab job openings in the United States as of September 2026, with employment types broken down into 83% Full Time, and 17% Contract. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $77,698 per year, or $37.4 per hour.

Data Science & Quantitative Analysis Expert

Remote

Weekday AI
Human Resources Consulting Services • 11 - 50 employees
Learn more about Weekday AIexternal

$60 - $90/hr

Part-time

Re-posted 17 days ago

Job description

This role is for one of our clients
Compensation: $60-$90 per hour
Join a pioneering AI initiative focused on developing the next generation of evaluation benchmarks for frontier AI models. We are seeking experienced Data Scientists and Quantitative Analysts to bring real-world analytical rigor to AI evaluation by designing sophisticated benchmark tasks based on practical data science workflows.
In this role, you will create complex, multi-step analytical challenges that mirror real research and business scenarios-from cleaning datasets and comparing statistical methods to interpreting results and presenting actionable insights. Working closely with AI researchers, you'll help identify where advanced AI models succeed, where they fail, and how evaluation benchmarks can better measure analytical reasoning.
This is a fully remote, full-time engagement requiring approximately 35 hours per week.
Requirements
Key Responsibilities
  • Design realistic data analysis challenges inspired by real-world research and analytical workflows, including data preparation, statistical modeling, hypothesis testing, and comparative analysis.
  • Develop reproducible reference analyses using Jupyter Notebooks or Google Colab, documenting methodologies and findings with clarity.
  • Create benchmark tasks that require objective comparisons between analytical techniques, supported by statistical validation and evidence-based recommendations.
  • Evaluate AI-generated analyses for correctness, statistical validity, reasoning quality, and interpretation accuracy.
  • Identify analytical errors, flawed assumptions, and reasoning gaps that experienced data professionals would immediately recognize.
  • Collaborate with AI researchers and fellow subject matter experts to improve benchmark quality, consistency, and analytical rigor.
Required Qualifications
  • Master's degree, PhD, or equivalent practical experience in Data Science, Statistics, Mathematics, Economics, Operations Research, or another quantitative STEM discipline.
  • Minimum 1 year of professional experience in research, research engineering, quantitative analysis, data science, or another data-intensive analytical role.
  • Strong hands-on experience with data cleaning, exploratory data analysis, statistical testing, correlation analysis, predictive modeling, and interpretation of analytical results.
  • Proficiency with Jupyter Notebooks or Google Colab for building reproducible analytical workflows.
  • Strong programming skills in Python, including experience with libraries such as pandas, NumPy, SciPy, scikit-learn, or similar analytical frameworks.
  • Working knowledge of Git and collaborative software development practices.
  • Excellent written communication skills with the ability to present analytical findings clearly to both technical and non-technical audiences.
  • Experience with AI evaluation, benchmark development, AI model assessment, or task authoring is preferred.
  • Exceptional analytical thinking, creativity, attention to detail, and the ability to solve complex, open-ended problems independently.
  • Ability to commit approximately 35 hours per week on a consistent basis.
Preferred Qualifications
  • Experience designing reproducible research workflows or analytical evaluation frameworks.
  • Familiarity with machine learning, large language models, or AI-assisted data analysis.
  • Background in benchmark design, statistical modeling, or quantitative research methodology.
  • Experience reviewing analytical work, mentoring analysts, or contributing to research publications.
Why Join
  • Help shape the future of AI by improving how advanced models are evaluated on real-world analytical reasoning.
  • Collaborate with leading AI researchers developing frontier evaluation benchmarks.
  • Apply your expertise in statistics and data science to advance AI reliability and decision-making capabilities.
  • Contribute directly to benchmark development that influences the evolution of next-generation AI systems.
  • Enjoy the flexibility of a fully remote engagement while working on impactful AI research initiatives.
Equal Opportunity
We are committed to fostering an inclusive and diverse environment where all qualified applicants receive equal consideration. Reasonable accommodations are available throughout the application and engagement process.
Contract & Engagement Details
  • Independent contractor engagement.
  • Fully remote with flexible working hours.
  • Expected commitment of approximately 35 hours per week.
  • Project duration may be extended, shortened, or concluded based on project requirements and individual performance.
  • Work does not require access to confidential or proprietary information from any current or former employer.
  • Payments are issued weekly based on approved work completed.
  • At this time, we are unable to support H1-B or STEM OPT candidates.

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