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Part Time Machine Learning Researcher Jobs (NOW HIRING)

This is a part-time, fully remote opportunity requiring approximately 20 hours per week ... Contributions to open-source ML/NLP projects or published research are a plus. * Experience working ...

Research Scholar

New York, NY · On-site

$27.77/hr

Description PART TIME RESEARCH SCHOLAR New York University Tandon School of Engineering Quantum ... Responsibilities include coding and running machine learning experiments, analyzing and ...

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Part Time Machine Learning Researcher information

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$30K

$113.1K

$164.5K

How much do part time machine learning researcher jobs pay per year?

As of Aug 4, 2026, the average yearly pay for part time machine learning researcher in the United States is $113,102.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,000.00 and $154,000.00 per year, depending on experience, location, and employer.

What skills and qualifications are needed to thrive as a part time machine learning researcher?

To thrive as a Part Time Machine Learning Researcher, you need a solid background in mathematics, statistics, and programming, often demonstrated through academic coursework or relevant research experience. Familiarity with programming languages like Python or R, machine learning libraries (e.g., TensorFlow, PyTorch), and version control systems such as Git is typically required. Strong analytical thinking, curiosity, and effective communication skills help in interpreting data and collaborating with research teams. These competencies enable researchers to design, implement, and present innovative solutions to complex problems in machine learning.

What does a part time machine learning researcher do?

A Part Time Machine Learning Researcher typically works on developing, testing, and improving machine learning models and algorithms, often as part of a research team or academic project. Their responsibilities may include data analysis, implementing machine learning techniques, conducting literature reviews, and contributing to research publications or presentations. Since the role is part-time, they usually work flexible hours and may balance these duties with other commitments such as studies or a different job. The position is ideal for students, professionals seeking experience, or those who wish to contribute to research while managing other responsibilities.

What is the difference between Part Time Machine Learning Researcher vs Data Scientist?

AspectPart Time Machine Learning ResearcherData Scientist
CredentialsTypically requires a master's or PhD in computer science, data science, or related fieldsOften requires a bachelor's or master's in data science, statistics, or related areas
Work EnvironmentResearch-focused, often in academic or R&D settings, with emphasis on developing new algorithmsBusiness-focused, working with large datasets to generate insights and support decision-making
Industry UsageCommon in research institutions, universities, and R&D departmentsWidely used across industries like finance, healthcare, tech, and marketing

While both roles involve working with machine learning, a Part Time Machine Learning Researcher primarily focuses on developing new algorithms and research, often in academic or research settings. In contrast, a Data Scientist applies machine learning techniques to analyze data and solve business problems. The roles share similar credentials but differ in work environment and industry application.

How do part time machine learning researchers balance independent work with collaboration within their research teams?

Part-time machine learning researchers often have flexible schedules, which means they need to be proactive in communicating with their teams and managing project timelines. While much of the research work can be done independently—such as data analysis, model development, and literature review—regular meetings and updates are essential to stay aligned with the team's goals. Many teams use collaborative platforms and version control systems to facilitate seamless contributions from part-time members. Clear documentation and open communication help ensure that part-time researchers can effectively integrate their work with the broader project and contribute meaningfully despite reduced hours.
More about Part Time Machine Learning Researcher jobs
What cities are hiring for Part Time Machine Learning Researcher jobs? Cities with the most Part Time Machine Learning Researcher job openings:
What are the most commonly searched types of Machine Learning Researcher jobs? The most popular types of Machine Learning Researcher jobs are:
What states have the most Part Time Machine Learning Researcher jobs? States with the most job openings for Part Time Machine Learning Researcher jobs include:
What job categories do people searching Part Time Machine Learning Researcher jobs look for? The top searched job categories for Part Time Machine Learning Researcher jobs are:
Infographic showing various Part Time Machine Learning Researcher job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 72% Full Time, 25% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $113,102 per year, or $54.4 per hour.

Fall 2026, Intern/Coop: Machine Learning Researcher

Raytheon Technologies

East Hartford, CT • On-site

Part-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 16 days ago


Job description

Date Posted:
2026-07-20
Country:
United States of America
Location:
US-CT-EAST HARTFORD-RTRC K ~ 411 Silver Ln ~ RTRC K
Position Role Type:
Hybrid
U.S. Citizen, U.S. Person, or Immigration Status Requirements:
Must be authorized to work in the U.S. without the company's immigration sponsorship now or in the future. The company will not offer immigration sponsorship for this position. The company will not seek an export authorization for this role.
Security Clearance Type:
None/Not Required
Security Clearance Status:
Not Required
Are you ready to explore the world of aerospace and defense? Do you want to learn from and collaborate with some of the greatest minds in the industry? At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on complex problems, advance your skills and create a safer, more connected world. Discover opportunities to make a difference at RTX.
At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Join us and help shape the future of aerospace and defense.
The Artificial Intelligence team researches and develops machine learning, computer vision, reinforcement learning, large language models and human computer interaction solutions for a variety of high impact real world problems in the aerospace, manufacturing and defense industries. Examples include autonomy, multi-agent coordination, cybersecurity, material discovery and design. We conduct basic and applied research in a stimulating multi-disciplinary environment where scientists, engineers, practitioners, and subject matter experts collaborate and exchange experience.
We are looking for fall interns/coops to support research on large language models, with primary emphasis on agentic AI, reasoning models and verification/evaluation frameworks for LLMs and agentic systems.
What You Will Do:
  • Develop methods and algorithms to evaluate, verify, and improve the reasoning, planning, and decision making of large language models and LLM-based agents.
  • Design and run experiments on GPU cluster, and benchmark performance against established baselines.
  • Explore approaches for agentic AI, including LLM agents that can plan, reason, and interact with tools and environments in a safe and reliable manner.
  • Detect and mitigate vulnerabilities such as hallucinations and jailbreaks.
  • Communicate research findings through presentations, technical reports, and contributions to top-tier publications.
  • Collaborate with a focused team on topics including safe and reliable LLM deployment, vulnerability detection, and LLM agents, gaining exposure to cutting-edge Generative AI applications

What You Will Learn:
  • Gain exposure to advanced research on LLMs and agentic systems, including planning, tool use, and interaction within complex environments.
  • Strengthen hands-on skills in large-scale model training, evaluation, verification and safe deployment practices.
  • Learn how to communicate research results effectively through presentations, technical writing, and potential contributions to top-tier AI/ML conferences.

Qualifications You Must Have:
  • Currently pursuing an MS/Ph.D. in Computer Science, Mathematics, or a related Engineering discipline. Candidates must work a minimum of 6 months in co-op role. Please submit a copy of your academic transcripts with your application.
  • 1+ years of MS/Ph.D.-level research experience in areas such as large language models, reasoning, post-training/fine-tuning techniques, robustness/vulnerability detection, formal verification
  • 1+ years of machine learning software development experience in Python, with familiarity in deep learning frameworks such as PyTorch or TensorFlow.

Qualifications We Prefer:
  • Publication record in top AI/ML venues such as NeurIPS, ICML, ICLR, ACL, or similar.
  • Demonstrated ability to set research direction, work independently, and contribute to collaborative team efforts.

Please ensure the role type defined below is appropriate for your needs before applying to this role. This position is classified as:
Hybrid: Employees who are working in Hybrid roles will work regularly both onsite and offsite. Ratio of time working onsite will be determined in partnership with your leader.
Candidates will learn more about role type and current site status throughout the recruiting process. For onsite and hybrid roles, commuting to and from the assigned site is the employee's personal responsibility.
As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote.
The salary range for this role is 37,000 USD - 82,000 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills.
Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement.
Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance.
This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply.
RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window.
RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act.
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