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Weekend No Experience Machine Learning Jobs in California

MM International

Machine Learning Engineer

Fremont, CA · On-site

Real-world experience deploying and maintaining machine learning solutions in production environments. * Passion for clean, sustainable, and modular code to bring research concepts to practical ...

Hive

Machine Learning Engineer

San Francisco, CA

$120K - $180K/yr

We value hard workers who have no qualms working with terabyte-scale datasets, who are interested ... Our ideal candidate has experience creating a working machine learning-powered project from the ...

Hive

Machine Learning Engineer

San Francisco, CA · On-site

$120K - $180K/yr

We value hard workers who have no qualms working with terabyte-scale datasets, who are interested ... Our ideal candidate has experience creating a working machine learning-powered project from the ...

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA · On-site

$9.7K/wk

We have an opening for a Machine Learning (ML) Bioengineer to conduct research training and ... Experience with high-performance computing, multi-node, multi-GPU, distributed training.

Unitytech

Machine Learning Engineer

San Francisco, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ... Working closely with experienced engineers and researchers, you'll contribute to systems that ...

Unitytech

Machine Learning Engineer

Mountain View, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ... Working closely with experienced engineers and researchers, you'll contribute to systems that ...

Quantcast

Machine Learning Engineer

San Francisco, CA · On-site

$151.30 - $178/hr

New Grad to 1 year of experience. * You must be work-authorized in the United States without the ... No relocation candidates at this time. * Fluency in Python, Java or similar programming languages.

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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 California?

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

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

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

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

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

Weekend No Experience Machine Learning jobs near you

Machine Learning Engineer

MM International

Fremont, CA • On-site

Contractor

Re-posted 21 days ago

Job description

Role: Machine Learning Engineer

Location: Fremont, CA 

 

once the documents are verified, a Codility assessment will be shared with the candidate, where they need to score a minimum of 70% and post that, a general video screening with PV. Then we send the submission to the client

About the Role:

Our direct client is hiring a Machine Learning Engineer for their software machine learning and computer vision team to design, develop, and implement critical machine learning models supporting factory and warehouse operations. You will transform ambiguous problem statements into robust end-to-end solutions using a variety of machine learning techniques and tools, including supervised learning, convolutional neural networks, and modern frameworks such as PyTorch and Pandas.

You will collaborate closely with partners in production, process, controls, and quality to deliver solutions for the most challenging problems in our operations. Your work will involve evaluating and deploying models in production environments, ensuring rapid and reliable alerting systems, and addressing operational issues as they arise. You must be adept at handling diverse, heterogeneous datasets that span multiple modalities, including images, multi-spectral sensor outputs, voice, text, and tabular data.

Responsibilities

  • Design, develop, and deploy machine learning models for factory and warehouse environments.
  • Collaborate with cross-functional teams to identify, define, and solve high-impact operational challenges.
  • Build and maintain end-to-end machine learning pipelines, from data collection and preprocessing to model deployment and monitoring.
  • Evaluate and compare models using statistical methods to ensure optimal performance and feasibility.
  • Ensure robust alerting and monitoring systems are in place for deployed models to address issues rapidly.
  • Work with diverse datasets, integrating multiple data types such as images, sensor data, voice, text, and tabular information.
  • Write clean, modular, and sustainable code to translate research ideas into production-ready solutions.

Minimum Requirements

  • In-depth knowledge of Python for high-performance, data-intensive applications.
  • Proficiency with at least one modern deep learning framework (e.g., PyTorch, Jax, TensorFlow).
  • Expertise in one or more of the following areas: computer vision, large language models, recommender systems, or operations research.
  • Foundational knowledge of statistics for model comparison and performance assessment.
  • Real-world experience deploying and maintaining machine learning solutions in production environments.
  • Passion for clean, sustainable, and modular code to bring research concepts to practical implementation.

Preferred Qualifications

  • CI/CD, Kubernetes, MLflow, TensorFlow, PyTorch, AWS.
  • Experience working in manufacturing, industrial automation, or warehouse environments.
  • Familiarity with multi-modal data integration and analysis.
  • Strong problem-solving skills and the ability to thrive in ambiguous, fast-paced settings.
  • Excellent communication skills for cross-functional teamwork.