ZipRecruiter

Log In

1

Research Assistant Machine Learning Jobs in Pasadena, CA

Hadrian

Machine Learning Engineer

Los Angeles, CA · On-site

Responsibilities : • Research, develop and deploy cutting-edge deep learning models, including ... the Machine Learning lifecycle - including the creation and optimization of production data ...

Hadrian

Machine Learning Engineer

Los Angeles, CA · On-site

Responsibilities : • Research, develop and deploy cutting-edge deep learning models, including ... the Machine Learning lifecycle - including the creation and optimization of production data ...

Hadrian Automation

Machine Learning Engineer

Torrance, CA · On-site

$160K - $250K/yr

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling ... Research, develop and deploy cutting-edge deep learning models, including OCR, vision-language, and ...

Machina Labs

Machine Learning Engineer

Los Angeles, CA

$160K - $190K/yr

This is a hands-on role for someone who thrives at the intersection of research and production ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

next page

Showing results 1-20

All JobsResearch Machine Learning JobsResearch Assistant Machine Learning JobsResearch Assistant Machine Learning Jobs in Pasadena, CA

Research Assistant Machine Learning information

See Pasadena, CA salary details

$9

$23

$34

How much do research assistant machine learning jobs pay per hour?

As of Aug 25, 2026, the average hourly pay for research assistant machine learning in Pasadena, CA is $23.90, according to ZipRecruiter salary data. Most workers in this role earn between $20.19 and $27.79 per hour, depending on experience, location, and employer.

What is a research assistant machine learning?

A Research Assistant in Machine Learning supports research projects by implementing algorithms, analyzing data, and conducting experiments to advance AI models. They assist senior researchers by preprocessing datasets, developing machine learning models, and evaluating their performance. Responsibilities may also include coding, literature reviews, and writing research papers. This role is typically found in academia, research labs, or industry R&D teams. Strong programming skills, statistical knowledge, and familiarity with ML frameworks like TensorFlow or PyTorch are essential.

What types of projects might a research assistant machine learning typically work on?

As a Research Assistant in Machine Learning, you may be involved in projects such as developing and evaluating predictive models, processing and analyzing large datasets, and assisting in the publication of research findings. Your work could contribute to applications like natural language processing, computer vision, or recommendation systems, depending on the focus of the research group. You’ll often collaborate closely with senior researchers, data scientists, or PhD students, allowing you to participate in brainstorming sessions, code development, and experimental design. This experience provides valuable exposure to cutting-edge technology and can serve as a strong foundation for a research or industry career in machine learning.

What are the key skills and qualifications needed to thrive as a research assistant machine learning?

To thrive as a Research Assistant Machine Learning, you need a solid understanding of machine learning algorithms, programming skills (especially in Python or R), and a background in statistics or computer science, often supported by a bachelor’s or master’s degree. Experience with frameworks such as TensorFlow, PyTorch, and data analysis tools, as well as familiarity with version control systems like Git, is highly beneficial. Strong problem-solving abilities, attention to detail, and effective communication skills help you excel in collaborative research environments. These skills ensure you can contribute meaningfully to research projects, analyze complex datasets, and communicate findings effectively within interdisciplinary teams.

What are popular job titles related to Research Assistant Machine Learning jobs in Pasadena, CA?

For Research Assistant Machine Learning jobs in Pasadena, CA, the most frequently searched job titles are:

What job categories do people searching Research Assistant Machine Learning jobs in Pasadena, CA look for?

The top searched job categories for Research Assistant Machine Learning jobs in Pasadena, CA are:

What cities near Pasadena, CA are hiring for Research Assistant Machine Learning jobs?

Cities near Pasadena, CA with the most Research Assistant Machine Learning job openings:

Research Assistant Machine Learning jobs near you
Infographic showing various Research Assistant Machine Learning job openings in Pasadena, CA as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $49,709 per year, or $23.9 per hour.

AI Research Assistant - Machine Learning & AI

Beverly Hills, CA • On-site, Remote

StudyFetch
See more jobs at StudyFetchexternal

$35 - $50/hr

Part-time

Posted 6 days ago

Job description

About Studyfetch
StudyFetch is the #1 AI-native learning platform globally, transforming how millions of students learn through personalized AI-powered education. We're growing fast with backing from top-tier investors and a mission that's redefining the future of education and ethical learning.
About the Role
We are looking for a highly motivated Master's student in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field to join our AI research team on a part-time basis.
Our research focuses primarily on the intersection of artificial intelligence and education, including the development and evaluation of AI systems that can improve teaching and learning. You will work directly with researchers and engineers on projects involving machine learning, generative AI, large language models, multimodal AI, educational data, model evaluation, and AI systems.
This is a hands-on research position. You will not simply be assisting with administrative research tasks-you will be expected to read papers, implement ideas, run experiments, analyze results, and contribute to the development of new research directions.
Depending on your interests and experience, your work may include developing and evaluating models, building research datasets, designing benchmarks and evaluation methodologies, reproducing published research, fine-tuning open-source models, analyzing educational data, and investigating novel applications of AI in education.
You will also contribute to the broader research development process, including identifying relevant research opportunities, analyzing RFPs and funding opportunities, and assisting with grant and research proposal development.
What You'll Do
  • Read and analyze recent research papers in machine learning, AI, and AI in education.
  • Implement and reproduce methods from recent research.
  • Design and conduct controlled experiments and ablation studies.
  • Train, fine-tune, and evaluate machine learning models.
  • Develop datasets and data-processing pipelines for AI research.
  • Build and maintain evaluation and benchmarking systems.
  • Analyze model performance and experimental results.
  • Investigate new approaches to improving AI capabilities, reliability, and effectiveness in educational settings.
  • Develop research prototypes in Python and modern ML frameworks.
  • Analyze educational datasets and student interaction data to identify research opportunities and patterns.
  • Document experiments, findings, and methodologies.
  • Collaborate with researchers and engineers to refine research hypotheses.
  • Contribute to technical reports, research papers, presentations, and potentially open-source projects.
  • Research and analyze RFPs, grant opportunities, and government or foundation funding programs relevant to AI and education.
  • Assist with the development of grant proposals, research proposals, technical narratives, and supporting materials.
  • Help identify research questions and proposed technical approaches that align with funding opportunities.
  • Track relevant developments in AI research, education technology, and government research priorities.

Areas of Research
Our research primarily focuses on the application and development of AI for education. Projects may span several areas, including:
  • Large Language Models (LLMs)
  • Generative AI
  • Multimodal AI
  • Computer vision
  • Natural language processing
  • AI tutoring and educational agents
  • Personalized learning
  • Student modeling and learning analytics
  • Model training and fine-tuning
  • Reinforcement learning and post-training
  • AI evaluation and benchmarking
  • Synthetic data generation
  • Representation learning
  • Retrieval-augmented generation (RAG)
  • Educational datasets and data infrastructure
  • AI safety, reliability, and evaluation in education

You do not need experience in all of these areas. Depth in one area, strong research fundamentals, and demonstrated ability to learn quickly are more important than breadth.
Required Qualifications
  • Currently pursuing or recently completed a Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, Statistics, Electrical Engineering, or a closely related field.
  • Strong foundation in machine learning and deep learning.
  • Strong Python programming skills.
  • Experience with at least one modern ML framework, preferably PyTorch.
  • Familiarity with fundamental concepts in neural networks, optimization, and statistical learning.
  • Ability to read and understand technical research papers.
  • Experience conducting technical or academic projects involving machine learning.
  • Strong analytical and problem-solving skills.
  • Strong written communication skills and the ability to clearly explain technical concepts.
  • Ability to work independently while collaborating closely with a research team.
  • Genuine interest in the application of AI to education.
Preferred Qualifications
  • Experience with LLMs, Transformers, multimodal models, computer vision, NLP, reinforcement learning, or generative AI.
  • Experience fine-tuning or training machine learning models.
  • Experience working with GPU-based ML environments.
  • Familiarity with Hugging Face Transformers or similar ML ecosystems.
  • Experience designing datasets, benchmarks, or model evaluations.
  • Experience reproducing results from published research.
  • Research experience through a Master's thesis, research lab, internship, or independent project.
  • Experience working with educational, student, or learning data.
  • Experience with AI evaluation, benchmarking, or experimental design.
  • Publications, preprints, conference submissions, or other demonstrated research output.
  • Contributions to open-source ML/AI projects.
  • Familiarity with Linux, Git, Docker, or distributed computing.
  • Experience researching or writing grant proposals, RFP responses, technical proposals, or research funding applications.
  • Familiarity with federal, state, foundation, or other research funding programs.

What We're Looking For
We're particularly interested in people who are curious, technically rigorous, and excited by the process of discovering something that doesn't already have an obvious answer.
The strongest candidates will be able to demonstrate that they have gone beyond simply completing coursework-for example, by:
  • Building and training their own models.
  • Reproducing a research paper.
  • Conducting an independent ML research project.
  • Developing a substantial Master's thesis.
  • Creating an interesting dataset or benchmark.
  • Investigating why a model succeeds or fails.
  • Working with real-world educational or student data.
  • Publishing or presenting research.
  • Contributing to an open-source ML project.
  • Writing or contributing to a research proposal or grant application.

You do not need to have published a paper to be successful in this role. We care more about your ability to think scientifically, write good code, design meaningful experiments, communicate clearly, and learn quickly.
We also value candidates who are interested in the broader research process-not just model development-including identifying research opportunities, understanding funding priorities, analyzing RFPs, and helping translate technical ideas into compelling research proposals.
Position Details
  • Position: Part-Time AI Research Assistant
  • Focus: Machine Learning & AI for Education
  • Hours: Approximately 15-25 hours per week
  • Location: [Remote / Hybrid]
  • Schedule: Flexible schedule designed to accommodate graduate coursework and research commitments
  • Compensation: $35-50/hour, depending on experience and qualifications

This position is designed for a graduate student who wants meaningful, hands-on experience conducting applied AI research in an industry research environment, with opportunities to contribute to research publications, funded research initiatives, datasets, benchmarks, and real-world AI systems.
#LI-SF1

Apply