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Junior Monitoring Evaluation Learning Jobs (NOW HIRING)

Synergie Systems

Junior AI Engineer

Phoenix, AZ · On-site

Junior AI Engineer Location: Phoenix, AZ Job Type: Only W2 · Develop and deploy AI/ML models for ... learning/LLM models when appropriate. · Implement model monitoring, evaluation, security, and ...

Q2Impact

Project Director

Washington, DC · On-site

The EAP Monitoring, Evaluation, and Learning (MEL) Platform supports the U.S. Department of State's Bureau of East Asian and Pacific Affairs (EAP), Office of Regional Assistance and Security Program ...

Q2Impact

Operations Manager

Washington, DC · On-site

The EAP Monitoring, Evaluation, and Learning (MEL) Platform supports the U.S. Department of State's Bureau of East Asian and Pacific Affairs (EAP), Office of Regional Assistance and Security Program ...

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How much do junior monitoring evaluation learning jobs pay per year?

As of Aug 22, 2026, the average yearly pay for junior monitoring evaluation learning 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 the difference between Junior Monitoring Evaluation Learning vs Monitoring and Evaluation Officer?

AspectJunior Monitoring Evaluation LearningMonitoring and Evaluation Officer
QualificationsBachelor's degree in social sciences, development studies, or related fieldsBachelor's or master's degree in similar fields, often with more experience
Work EnvironmentEntry-level, supporting M&E activities under supervisionMore independent, overseeing M&E processes and reporting
ResponsibilitiesData collection, assisting in evaluations, supporting learning activitiesDesigning M&E frameworks, analyzing data, preparing reports

In summary, Junior Monitoring Evaluation Learning roles are typically entry-level positions focused on supporting M&E tasks, while Monitoring and Evaluation Officers have more responsibility, independence, and experience in managing M&E systems and reporting.

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Junior Monitoring Evaluation Learning jobs near you
Infographic showing various Junior Monitoring Evaluation Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $71,799 per year, or $34.5 per hour.

Junior AI Engineer

Synergie Systems

Phoenix, AZ • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

Job Title: Junior AI Engineer

Location: Phoenix, AZ

Job Type: Only W2

Job Description:

·       Develop and deploy AI/ML models for business applications.

·       Build Generative AI and LLM-based applications using models such as GPT, Claude, Gemini, or open-source LLMs.

·       Develop RAG (Retrieval-Augmented Generation) pipelines using embeddings and vector databases.

·       Design AI agents, intelligent automation, and AI-powered workflows.

·       Prepare, clean, transform, and analyze datasets for model development.

·       Develop APIs and backend services for AI applications.

·       Fine-tune, evaluate, and optimize machine-learning/LLM models when appropriate.

·       Implement model monitoring, evaluation, security, and performance optimization.

·       Deploy AI applications using AWS, Azure, or Google Cloud.

·       Use Docker, Kubernetes, CI/CD, and MLOps practices for production deployment.

·       Collaborate with software engineers, data scientists, product managers, and business stakeholders.

·       Troubleshoot model, application, data, and production issues.

Technical Skills:

·       Python — strong proficiency

·       Machine Learning and Deep Learning

·       Generative AI / LLMs

·       Prompt engineering and LLM evaluation

·       RAG and vector databases

·       REST APIs / FastAPI

·       SQL and database fundamentals

·       Git/GitHub

·       Linux

·       Docker

·       Cloud platforms: AWS / Azure / Google Cloud Platform

·       Familiarity with PyTorch or TensorFlow

·       Understanding of NLP and/or computer vision

·       Basic MLOps and CI/CD concepts

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