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Research Assistant Machine Learning Jobs in Brighton, MA

Generalist

Research Assistant

Somerville, MA · On-site

$50 - $70/hr

We are looking for a Research Assistant to help design, run, and analyze experiments at the intersection of machine learning and robotics. This is an entry‑level research role for individuals with ...

NorthEastern

Research Assistant

Boston, MA · On-site

$48K - $66K/yr

About the Opportunity The Research Assistant (Neuroinformatics) in the Computational Optics and ... A solid foundation in machine learning, large-data processing and software development, including ...

MatrixSpace

Machine Learning Engineer

Burlington, MA · Remote

$165K - $200K/yr

Help us bridge machine learning research and real-world deployment! MatrixSpace develops AI-enabled radar and sensing systems that help people understand what's happening in the world around them. By ...

Modulate

Machine Learning Engineer

Somerville, MA · On-site

$170 - $200/hr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice ... You'll work closely with researchers, engineers, product leaders, and executives to bring ...

New

Bracebridge Capital

Machine Learning Analyst

Boston, MA · On-site

$110K - $145K/yr

The work is highly collaborative and spans quantitative research, software engineering, and machine ... Since the team works closely with trading floor personnel to assist with portfolio management ...

Bracebridge Capital

Machine Learning Analyst

Boston, MA · On-site

$110K - $145K/yr

The work is highly collaborative and spans quantitative research, software engineering, and machine ... Since the team works closely with trading floor personnel to assist with portfolio management ...

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

As of Sep 6, 2026, the average hourly pay for research assistant machine learning in Brighton, MA is $23.88, 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 job categories do people searching Research Assistant Machine Learning jobs in Brighton, MA look for?

The top searched job categories for Research Assistant Machine Learning jobs in Brighton, MA are:

What cities near Brighton, MA are hiring for Research Assistant Machine Learning jobs?

Cities near Brighton, MA 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 Brighton, MA as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $49,665 per year, or $23.9 per hour.

Research Assistant

Generalist

Somerville, MA • On-site

$50 - $70/hr

Other

Posted 4 days ago

Key responsibilities

  • Run structured experiments on robot platforms and collect high-quality data while tracking experimental conditions

  • Design evaluation tasks, prepare physical setups, and troubleshoot hardware or procedural issues

  • Analyze experimental results to assess model improvements, ensure repeatability, and communicate findings clearly

Job description

About the Role:

We are looking for a Research Assistant to help design, run, and analyze experiments at the intersection of machine learning and robotics. This is an entry‑level research role for individuals with less than 3 years of research experience, and is designed to be a potential career path towards eventually contributing as a Research Scientist.

At Generalist, we are building foundation models for robots. These models improve through a tight feedback loop: design experiments, collect data, train or fine‑tune models, evaluate them in the real world, analyze results, and repeat. This role helps make that loop faster, more rigorous, and more reliable.

You will work closely with ML researchers and robotics engineers to run robot experiments, design evaluation tasks, brainstorm ideas, collect data, interpret results, and document repeatable workflows.

A major part of this role is helping ensure our evaluations are trustworthy. We care deeply about experimental design, controls, hands‑on iteration, sample sizes, variance, repeatability, and statistical rigor.

You’ll be responsible for:

  • Running structured experiments on robot platforms

  • Setting up physical tasks, materials, fixtures, and benchmarks for robot evaluations

  • Collecting high‑quality robot data and tracking experimental conditions

  • Measuring real‑world success rates across tasks, robots, and model variants

  • Designing evaluations with attention to controls, repeatability, statistical rigor, and sources of bias

  • Analyzing results to help distinguish real model improvements from noise

  • Synthesizing findings and communicating them clearly to ML researchers and engineers

  • Preparing robots, sensors, workspaces, and materials for rollouts and evaluations

  • Helping kick off training jobs, run evaluations, and organize results

  • Beta testing internal and third‑party tools for teaching robots new skills

  • Troubleshooting physical setups, hardware issues, and procedural bottlenecks

  • Writing clear documentation and playbooks so others can reproduce workflows

  • Improving experimental reliability, data quality, and operational throughput over time

You might thrive in this role if you:

  • Have experience running experiments, lab studies, field studies, data collection workflows, or structured evaluations

  • Think carefully about experimental design, confounding factors, controls, sample sizes, variance, and what conclusions the data can actually support

  • Are diligent and detail‑oriented, especially when tasks are repetitive but subtle differences matter

  • Enjoy hands‑on work with physical systems, equipment, materials, or instruments

  • Are comfortable following protocols while also noticing when something is wrong or could be improved

  • Can coordinate many moving parts: robots, materials, tasks, data, model versions, metrics, and documentation

  • Communicate clearly and can summarize what happened, what changed, and what the evidence suggests

  • Are curious about machine learning and robotics, even if you are not yet an expert in either

  • Have some exposure to programming, data analysis, robotics, hardware, electronics, mechanical assembly, or experimental tooling

  • Prefer fast iteration, careful measurement, and empirical progress over abstract theory alone

We are an equal‑opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

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