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Research Assistant Machine Learning Jobs in Randolph, MA

ICONSTAFF

Machine Learning Engineer

Cambridge, MA · On-site +1

Machine Learning Engineer - Computer Vision & Robotics Tycho.AI is redefining the future of ... Stay current on research and apply state-of-the-art techniques in autonomy and perception.

Alsym Energy

Machine Learning Engineer (Malden)

Malden, MA · On-site

$130K - $215K/yr

Master's or PhD in Computer Science, Machine Learning, AI, Engineering, or a related scientific ... Research experience in causal reasoning, probabilistic programming, or symbolic AI. * Familiarity ...

C the Signs

Senior Machine Learning Engineer

Boston, MA · Remote

$125K - $165K/yr

Research & Development: Stay up-to-date with the latest advancements in machine learning and healthcare AI, and explore new technologies and methodologies to enhance our solutions. * Documentation:

C the Signs

Senior Machine Learning Engineer

Boston, MA · On-site +1

$133K - $175K/yr

Research & Development: Stay up-to-date with the latest advancements in machine learning and healthcare AI, and explore new technologies and methodologies to enhance our solutions. * Documentation:

Crowe LLP

Machine Learning Intern

Boston, MA · On-site

$27 - $42/hr

Modeling Understanding how to frame business problems as data science problems Navigating the full data science lifecycle: research and exploration, development, deployment, support Using correct ...

STR

Machine Learning Engineer

Woburn, MA

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML ... Working as part of a multidisciplinary team of researchers, engineers, and domain experts, you will ...

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Research Assistant Machine Learning information

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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 Randolph, MA is $22.34, according to ZipRecruiter salary data. Most workers in this role earn between $18.89 and $25.96 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 cities near Randolph, MA are hiring for Research Assistant Machine Learning jobs?

Cities near Randolph, 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 Randolph, MA as of August 2026, with employment types broken down into 1% As Needed, 68% Full Time, 28% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $46,468 per year, or $22.3 per hour.

Senior Research Scientist, Robotics Research

Toyota Research Institute

Cambridge, MA • On-site

$180K - $258K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 17 days ago

Key responsibilities

  • Work as part of a research team building useful robots and general-purpose robot foundation models.

  • Implement, extend, and create state-of-the-art methods for robot behavior learning from interactive embodied data and online data sources.

  • Design and implement high-performance machine-learning pipelines and optimize data and learning stacks for scalability, efficiency, and performance.

Job description

At Toyota Research Institute (TRI), we’re on a mission to improve the quality of human life. We’re developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we’ve built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences.


The Vision
We envision a future with robots that help people in our real environments with interactions that allow robots to understand, adapt, and grow with us. We believe that robots should and will work well alongside people: helping where wanted, and ultimately enabling people to spend more time on the activities they enjoy most. To achieve this, robots need to be able to operate reliably in messy, unstructured environments. We must also create robots that people can understand, collaborate with, and rely on.

The Team
Our goal is to revolutionize the field of robotics, enabling long-horizon dexterous behaviors to be efficiently taught, learned, and improved over time in diverse, real-world environments with people.Our team has deep cross-functional expertise across hardware, simulation, perception, controls, and machine learning. We measure our success in terms of fundamental capabilities development, as well as research impact via open-source software and publications. Come join us and let’s make general-purpose robots a reality.
 
Some of our ongoing work is highlighted here.

The Opportunity
We’re looking for a driven researcher with a “make it happen” mentality. The ideal candidate is able to operate independently when needed, but works well as part of a larger integrated group at the cutting edge of state-of-the-art robotics and machine learning. If our mission of revolutionizing robotics through machine learning resonates with you, get in touch and let’s talk about how we can create the next generation of AI-powered capable robots together!
 
Responsibilities
  • Work as part of a dynamic, closely-knit research team building useful robots and general-purpose robot foundation models.
  • Implement, extend, and create state-of-the-art methods for robot behavior learning from a mixture of interactive embodied data and online data sources.
  • Design and implement high-performance machine-learning pipelines and optimize data and learning stacks for scalability, efficiency, and performance.
  • Be a key member of the team and play a critical role in rapid progress measured by both the development of internal capabilities and high-impact external publication.
  • Collaborate with internal research scientists and our partner labs at top academic research universities including MIT, Stanford, Berkeley, CMU, Columbia, and Princeton to drive pioneering research at scale.
Qualifications
  • PhD in computer science, machine learning, robotics, or a closely related field.
  • Experience training large models and deploying them on embodied systems, particularly toward robotic manipulation.
  • Strong software development skills in Python, familiarity with mixed C++/Python codebases, and a focus on clean, maintainable code.
  • Extensive practical experience with Machine Learning using a major framework such as PyTorch or TensorFlow. Familiarity with data pipelines, model serving and optimization, cloud training, and dataset management.
  • Strong understanding of the state-of-the-art in robot learning, including generative models (e.g., diffusion policy, flow matching), reinforcement learning, and/or world models.
  • Practical experience with robots and the system integration challenges inherent in conducting research and deploying onto physical hardware platforms.
  • An ability to move fast and switch between modes of rapid prototyping and robust implementation as required.
  • A strong track record of impact, either via first author research publications at top-tier machine learning or robotics conferences (RSS, NeurIPS, ICML, CoRL, ICRA, IROS, …), or via meaningful contributions to successful industry initiatives.
Bonus Qualifications
  • Experience in robotics and machine learning research or related projects in an industry setting.
  • Experience with robotic middleware such as ROS 2 and common communication methods and protocols.
  • Experience with modern ML infrastructure pipelines, approaches, and tools.
  • Experience with VR-based teleoperation for real-time robot control.
  • Background or familiarity with some of the following: motion control and actuation, whole-body control, reinforcement learning, robot teleoperation methods, common communication protocols, research robotic arms/systems, visual perception and depth sensors, machine learning, robotic simulation, force and tactile sensing systems, haptic interfaces.
The pay range for this position at commencement of employment is expected to be between $180,000 and $258,750/year for Massachusetts-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, a candidate's experience, skills, job-related knowledge, and market location. TRI offers a generous benefits package including medical, dental, and vision insurance, 401(k) eligibility, paid time off benefits (including vacation, sick time, and parental leave), and an annual cash bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer of employment.

Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information.
 
TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant’s race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws.
 
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.