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Weekend No Experience Machine Learning Jobs in Ohio

Senior Machine Learning Engineer

Cincinnati, OH · On-site

$100K - $137K/yr

We are seeking an experienced Machine Learning Engineer with a strong bias for action, an ownership mindset, and a passion for solving complex business problems through automation and AI. The ideal ...

In this role, you will work alongside experienced engineers and data scientists to build, deploy, and maintain machine learning models. This is an excellent opportunity for someone early in their ...

In this role, you will work alongside experienced engineers and data scientists to build, deploy, and maintain machine learning models. This is an excellent opportunity for someone early in their ...

In this role, you will work alongside experienced engineers and data scientists to build, deploy, and maintain machine learning models. This is an excellent opportunity for someone early in their ...

$75 - $95/hr

... Unternehmen. Als Machine Learning Engineer (m/w/d) bei Synnio entwickelst und betreibst du ... TensorFlow, PyTorch, Scikit-Learn). * Erfahrung im Daten-Engineering (ETL, Datenaufbereitung ...

ClifyX is a company that specializes in AI solutions, and they are seeking a Machine Learning ... Required : • Strong hands on experience with Core ML & Stats (optimization, supervised ...

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... No commuting required. * Get matched with students best-suited to your teaching style and expertise.

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... No commuting required. * Get matched with students best-suited to your teaching style and expertise.

Machine Learning Tutor

Akron, OH · Remote

$18 - $40/hr

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... No commuting required. * Get matched with students best-suited to your teaching style and expertise.

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... No commuting required. * Get matched with students best-suited to your teaching style and expertise.

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Weekend No Experience Machine Learning information

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 are the key skills and qualifications needed to thrive as a weekend no experience machine learning professional?

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 starting a weekend no experience machine learning role?

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 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.

What are popular job titles related to Weekend No Experience Machine Learning jobs in Ohio?

For Weekend No Experience Machine Learning jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Weekend No Experience Machine Learning jobs in Ohio look for?

The top searched job categories for Weekend No Experience Machine Learning jobs in Ohio are:

What cities in Ohio are hiring for Weekend No Experience Machine Learning jobs?

Cities in Ohio with the most Weekend No Experience Machine Learning job openings:

Senior Machine Learning Engineer

TUPPL Technology Inc

Cincinnati, OH • On-site

$100K - $137K/yr

Other

Posted 5 days ago


Job description

Role : Senior Machine Learning Engineer

Location: Cincinnati OH

Full-Time 

We are seeking an experienced Machine Learning Engineer with a strong bias for action, an ownership mindset, and a passion for solving complex business problems through automation and AI. The ideal candidate demonstrates technical excellence, leads by example, and has proven experience delivering enterprise-grade machine learning and Generative AI solutions in regulated environments.

Key Responsibilities

  • Design, develop, deploy, and maintain scalable machine learning and Generative AI solutions with a focus on reliability, performance, security, and business value.
  • Champion an automation-first approach to software and AI engineering, identifying opportunities to improve operational efficiency and reduce manual processes.
  • Build and operationalize machine learning models and AI-enabled applications throughout the entire model lifecycle, from experimentation to production deployment and monitoring.
  • Develop and deploy Generative AI applications in production environments, preferably within financial services or other highly regulated industries.
  • Apply and advocate Responsible AI principles, ensuring solutions meet requirements for fairness, explainability, transparency, privacy, security, and compliance.
  • Perform model risk evaluations, complete required governance documentation and questionnaires, and partner with stakeholders to address and remediate identified risks.
  • Establish and maintain frameworks for MLOps, model lifecycle management, monitoring, validation, version control, auditability, and AI governance.
  • Collaborate with Risk, Compliance, Information Security, and business partners to ensure machine learning solutions meet enterprise and regulatory standards.
  • Implement CI/CD pipelines, automated testing, model monitoring, observability, and production support processes for machine learning applications.
  • Evaluate emerging machine learning and AI technologies and recommend appropriate adoption strategies.
  • Mentor team members on best practices in machine learning engineering, MLOps, Responsible AI, and production AI systems.

Required Qualifications

  • Extensive experience designing, developing, and deploying machine learning solutions in production environments.
  • Hands-on experience developing and deploying Generative AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, and modern AI development frameworks.
  • Strong understanding of machine learning model development, feature engineering, model evaluation, performance optimization, and model monitoring.
  • Experience conducting model risk assessments and supporting governance, compliance, and validation requirements within regulated environments.
  • Practical experience implementing MLOps practices including model deployment, versioning, monitoring, automated retraining, and CI/CD pipelines.
  • Strong understanding of Responsible AI, model explainability, governance, and risk management concepts.
  • Proficiency in Python and modern machine learning ecosystems, including frameworks such as TensorFlow, PyTorch, Scikit-learn, LangChain, Semantic Kernel, or equivalent technologies.
  • Strong communication, problem-solving, and stakeholder management skills.