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Volunteer Junior Machine Learning Engineer Jobs (NOW HIRING)

Pennant Solutions Group

$77K - $105K/yr

Senior Machine Learning Engineer Position Type: Full-Time/Onsite in Richmond, VA - NO REMOTE Level ... mentoring junior team members and establishing best practices across the organization. Key ...

Tapestry

Machine Learning Engineer

Mountain View, CA · On-site

About the role: We're looking for an early career Machine Learning Engineer to join our team. In this role you will build and deploy state of the art machine learning models to solve complex ...

1 point system

Machine Learning Engineer

Fort Mill, SC · Remote

$48/hr

Job Title Machine Learning Engineer Location Remote Rate $48/hr on W2 Must Haves: Neaural networks NLP Python AZURE Pytorch or tensorflow Machine Learning Engineer / AI Engineer Role Role Overview ...

Tapestry

Machine Learning Engineer

Mountain View, CA · On-site

About the role: We're looking for an early career Machine Learning Engineer to join our team. In this role you will build and deploy state of the art machine learning models to solve complex ...

Constellation Space

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

The Role We are looking for a Machine Learning Engineer to bridge the gap between AI research and production-grade flight systems. You will optimize, deploy, and scale machine learning models that ...

Quantum Machines

Machine Learning Engineer

We are looking for a Machine Learning Engineer to design, build, and deploy machine learning systems that improve the calibration, control, and operation of quantum processors. In this role, you will ...

Rapidtrade

Senior Machine Learning Engineer

Manhattan, NY · On-site

$115K - $158K/yr

Mentor junior engineers and contribute to engineering best practices * Research and evaluate new ML techniques and frameworks What We're Looking For * 5+ years of experience in machine learning or ...

Givzey

Machine Learning Engineer

Machine Learning Engineer We're looking for a talented and motivated Machine Learning Engineer to join our team and help develop cutting-edge AI solutions. In this role, you'll have the opportunity ...

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Volunteer Junior Machine Learning Engineer information

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$33.5K

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How much do volunteer junior machine learning engineer jobs pay per year?

As of Sep 12, 2026, the average yearly pay for volunteer junior machine learning engineer in the United States is $71,799.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,500.00 and $80,000.00 per year, depending on experience, location, and employer.

What is a volunteer junior machine learning engineer?

Volunteer Junior Machine Learning Engineers are individuals who offer their time and skills, often without pay, to assist in machine learning projects. They typically have foundational knowledge in programming, data analysis, and machine learning concepts, and they work under the guidance of experienced engineers or data scientists. Their responsibilities may include data preprocessing, building and testing models, and supporting research or development efforts. These roles provide valuable hands-on experience and are often sought after by students or career changers looking to break into the field.

What types of projects and tasks can a volunteer junior machine learning engineer expect to work on, and how do these contribute to skill development?

As a Volunteer Junior Machine Learning Engineer, you will typically assist with data preparation, exploratory data analysis, and building or improving basic machine learning models under the supervision of more experienced engineers. You may also help with tasks such as cleaning datasets, implementing algorithms, and evaluating model performance. These projects are designed to provide hands-on experience and mentorship, helping you develop technical skills while learning collaborative workflows in a team setting. This role is a great opportunity to build your portfolio, gain real-world experience, and network within the machine learning community.

What are the key skills and qualifications needed to thrive as a volunteer junior machine learning engineer, and why are they important?

To thrive as a Volunteer Junior Machine Learning Engineer, you need a foundational understanding of programming (especially Python), mathematics, and basic machine learning concepts, often supported by coursework or online certifications. Familiarity with tools like TensorFlow, scikit-learn, Jupyter Notebooks, and version control systems like Git is usually expected. Curiosity, teamwork, and strong problem-solving skills help you learn quickly and contribute effectively in a collaborative environment. These skills and qualities ensure you can support real projects, continue developing your expertise, and add value even at an entry or volunteer level.

What is the difference between Volunteer Junior Machine Learning Engineer vs Volunteer Data Analyst?

AspectVolunteer Junior Machine Learning EngineerVolunteer Data Analyst
Required CredentialsBasic programming, introductory ML knowledge, possibly some courseworkData analysis skills, Excel, SQL, basic statistics
Work EnvironmentTech-focused projects, coding, model developmentData interpretation, reporting, visualization
Employer & Industry UsageTech companies, research projects, startupsNonprofits, research institutions, business analytics

The Volunteer Junior Machine Learning Engineer and Volunteer Data Analyst roles both involve working with data, but the ML engineer focuses on developing machine learning models and algorithms, requiring some programming and ML knowledge. The Data Analyst primarily interprets data through visualization and reporting, often using tools like Excel and SQL. Both roles are valuable in various industries, but the ML engineer role emphasizes technical model development, while the Data Analyst role centers on data interpretation and communication.

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Cities with the most Volunteer Junior Machine Learning Engineer job openings:

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Volunteer Junior Machine Learning Engineer jobs near you
Infographic showing various Volunteer Junior Machine Learning Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 22% Part Time, and 2% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $71,799 per year, or $34.5 per hour.

Machine Learning Engineer

Washington, DC

AI Squared
See more jobs at AI Squaredexternal

Full-time

Re-posted 24 days ago

Job description

Machine Learning Engineer
Washington, DC (Hybrid)

About the Role:

We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying, maintaining, and monitoring the AI/ML systems that power our platform. You will work closely with data scientists, data engineers, and product teams to ensure scalable, reliable, and production-grade AI solutions. You'll play a critical role in operationalizing large language models (LLMs) and other ML systems, ensuring they run efficiently, securely, and with robust monitoring in place.

Key Responsibilities:
  • Design, implement, and maintain ML deployment pipelines for scalable production systems.
  • Operationalize large language models (LLMs) and other AI/ML models, ensuring high availability and reliability.
  • Build robust model monitoring, logging, and alerting systems to track performance and detect drift.
  • Partner with data scientists to transition models from research/prototype into production-ready deployments.
  • Develop CI/CD pipelines for ML workflows, integrating testing, validation, and automated deployment.
  • Optimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed systems.
  • Apply containerization and orchestration (Docker, Kubernetes) to enable reproducible, scalable systems.
  • Collaborate with cross-functional teams to ensure ML systems align with platform goals and business requirements.
Qualifications:
  • 5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar role.
  • Proven experience deploying and maintaining machine learning models in production at scale.
  • Hands-on experience with ML lifecycle tooling (MLflow, Kubeflow, SageMaker, Vertex AI, or similar).
  • Strong proficiency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow.
  • Deep knowledge of containerization (Docker) and orchestration (Kubernetes) for production ML systems.
  • Expertise with cloud platforms (AWS, GCP, Azure) for ML deployment and scaling.
  • Strong understanding of MLOps best practices, monitoring, and automation.
  • Excellent problem-solving skills, with an emphasis on building reliable, scalable systems.
  • Strong communication and collaboration skills across technical and non-technical teams.

Apply