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Weekend No Experience Machine Learning Jobs (NOW HIRING)

You will work on real-world projects, collaborate with experienced professionals, gain valuable ... of machine learning and deep learning algorithms. Familiarity with training or fine-tuning large ...

Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug ... Experience doing research and working with interdisciplinary teams Additional Preferred Experience ...

Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug ... Experience doing research and working with interdisciplinary teams Additional Preferred Experience ...

... no experience required with an advance degree (MS or PhD) * Strong foundation in supervised and unsupervised learning and statistical modeling. * Experience with Python ML frameworks (e.g ...

Experience in other programming languages (eg. Java, R, Haskell) a plus. * Solid knowledge of machine learning tools (eg. scikit-learn, tensorflow, keras, pytorch, Spark MLlib) required. * Experience ...

Experience in other programming languages (eg. Java, R, Haskell) a plus. * Solid knowledge of machine learning tools (eg. scikit-learn, tensorflow, keras, pytorch, Spark MLlib) required. * Experience ...

Proven experience as a Machine Learning Engineer or in a similar role. * Strong proficiency in ... programming languages such as Python, R, or Java. * Experience with machine learning frameworks and ...

Experience working with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn * Experience deploying or supporting machine learning models in production environments * Experience ...

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Weekend No Experience Machine Learning information

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How much do weekend no experience machine learning jobs pay per hour?

As of May 31, 2026, the average hourly pay for weekend no experience machine learning in the United States is $17.98, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $18.27 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning professional with no prior experience working weekends, and why are they important?

To thrive as a Machine Learning professional, foundational knowledge in mathematics, statistics, and programming (especially Python) is essential, typically demonstrated through coursework or self-directed learning. Familiarity with machine learning libraries such as scikit-learn or TensorFlow and version control systems like Git is highly beneficial, even at an entry level. Curiosity, problem-solving abilities, and effective communication help newcomers stand out as they learn quickly and collaborate with more experienced team members. These skills and qualities are crucial to building practical expertise, contributing to projects, and adapting to the evolving demands of machine learning roles.

What kind of support and training can I expect as someone starting a weekend machine learning role with no prior experience?

In a weekend machine learning role designed for beginners, you can typically expect onboarding sessions, access to online learning materials, and mentorship from more experienced team members. Many organizations provide structured guidance through tutorials, code reviews, and collaborative projects to help you build foundational skills. You’ll likely be assigned manageable tasks that allow you to gradually familiarize yourself with real datasets and tools, while regular feedback ensures your steady progress. Team meetings and open communication channels are common, so don’t hesitate to ask questions and seek help as you learn.

What is a Weekend No Experience Machine Learning job?

A Weekend No Experience Machine Learning job is a part-time opportunity typically scheduled on weekends for individuals interested in machine learning but who have little or no prior experience in the field. These jobs are designed for beginners and may involve tasks such as data labeling, assisting with simple coding projects, or supporting research teams. They provide a great entry point for those looking to gain hands-on experience, learn industry tools, and build their resumes while balancing other commitments like school or a full-time job.

What is the difference between Weekend No Experience Machine Learning vs Weekend Data Analyst?

AspectWeekend No Experience Machine LearningWeekend Data Analyst
Required CredentialsBasic understanding of programming, no formal certification neededBasic knowledge of data analysis tools, possibly some certifications
Work EnvironmentProject-based, flexible hours, often remotePart-time, flexible hours, often remote or on-site
Industry UsageTech, finance, healthcare, startupsBusiness, marketing, finance, consulting

Weekend No Experience Machine Learning roles focus on introductory tasks like data preprocessing and basic model training, suitable for beginners. Weekend Data Analyst positions involve analyzing datasets, creating reports, and supporting decision-making. Both roles are flexible and often part-time, but they differ in technical depth and industry focus.

More about Weekend No Experience Machine Learning jobs
What cities are hiring for Weekend No Experience Machine Learning jobs? Cities with the most Weekend No Experience Machine Learning job openings:
What states have the most Weekend No Experience Machine Learning jobs? States with the most job openings for Weekend No Experience Machine Learning jobs include:
What job categories do people searching Weekend No Experience Machine Learning jobs look for? The top searched job categories for Weekend No Experience Machine Learning jobs are:
Infographic showing various Weekend No Experience Machine Learning job openings in the United States as of May 2026, with employment types broken down into 77% Full Time, 8% Part Time, and 15% Contract. Highlights an 94% Physical, and 6% Remote job distribution, with an average salary of $37,403 per year, or $18 per hour.
Machine Learning Intern

Machine Learning Intern

EarnIn

Mountain View, CA • Hybrid

$40/hr

Other

Posted 22 days ago


Job description

POSITION SUMMARY

As a Fintech company where Machine Learning (ML) is one of the key drivers of growth, our operations highly rely on machine learning models, from business decisions to customer experiences. Therefore, building and deploying state-of-the-art machine learning systems to drive impact via our data capabilities is key. To guarantee the success of machine learning systems, we need to provide a detailed formulation, extensive experimentation, and to transform ML models into high-performance production-level code, including not only implementing sophisticated machine learning algorithms but also robustness monitoring and system logging/alarming. 

 We seek talented and motivated students and recent graduates with a strong background in machine learning, deep learning, language models and generative AI, programming, and data analysis to join our 12-week Machine Learning Internship Program. You will work on real-world projects, collaborate with experienced professionals, gain valuable experience in the fintech industry, and realize business and social impact. This role requires hybrid work from our Mountain View office, with 2 days a week in person. This internship will pay $40 per hour, with an expected 40 hours per week for the 12-week program. We are unable to provide visa sponsorship or immigration support for this position.  

WHAT YOU'LL DO 

  • Train and fine-tune large-scale Foundation Models to support various fintech product use cases
  • Work with a large dataset, including structured and unstructured data
  • Help in ensuring improvements in our current ML systems via model, data, or experimentation upgrades
  • Gain hands-on experience with a wide array of technologies, including PyTorch, AWS, Kafka, Databricks, etc

WHAT WE'RE LOOKING FOR

  • Actively pursuing a Master's or PhD in Computer Science, Information Technology, or a related field
  • Located in Mountain View, or have the ability to relocate there, for the duration of the internship 
  • Strong understanding of statistical models, familiarity, and in-depth understanding of machine learning and deep learning algorithms. Familiarity with training or fine-tuning large-scale models, Sequence Transformer models 
  • Interest in multimodal or multitask learning across structured, sequential, and behavioral data
  • Familiarity with AI tools, harness engineering, agentic workflow, etc.
  • Hands-on programming experience in Python and ML frameworks such as PyTorch
  • Equipped with good verbal and written communication skills
  • A background demonstrating strong problem-solving skills
  • Committed to taking ownership of projects, conducting thorough investigations, and driving initiatives to conclusion

#LI-Hybrid