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How much do ml research assistant jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for ml research assistant in the United States is $21.91, according to ZipRecruiter salary data. Most workers in this role earn between $18.51 and $25.48 per hour, depending on experience, location, and employer.

What is an ML Research Assistant?

ML Research Assistants are individuals who support machine learning research projects by assisting with tasks like data collection and preprocessing, literature reviews, experimental setup, model training, and result analysis. They often collaborate with researchers, graduate students, and professors to advance the development and understanding of machine learning algorithms. ML Research Assistants may also help write research papers, prepare presentations, and maintain codebases. This role is common in academic, research, and industry settings, and serves as valuable experience for those interested in pursuing advanced studies or careers in artificial intelligence.

What skills and qualifications are needed to thrive as an ML Research Assistant?

To thrive as an ML Research Assistant, you need a solid background in mathematics, programming (Python, R), and a foundational understanding of machine learning concepts, often demonstrated by a relevant degree or coursework in computer science or data science. Familiarity with technical tools such as TensorFlow, PyTorch, Jupyter Notebooks, and version control systems like Git is crucial. Strong analytical thinking, attention to detail, and effective communication skills help you interpret research findings and collaborate within a team. These skills are vital to effectively support complex ML projects, contribute to innovative research, and ensure accurate, reproducible results.

What are common challenges faced by ML Research Assistants when collaborating with senior researchers and engineers?

ML Research Assistants often face the challenge of bridging the gap between theoretical research and practical implementation, especially when collaborating with experienced researchers and engineers. Communication can be complex, as they may need to translate high-level research goals into experimental setups or prototype code. Additionally, ML Research Assistants must stay adaptable, as project priorities can shift quickly based on new findings or feedback. Building strong documentation and proactive communication skills are key to ensuring seamless collaboration within multidisciplinary teams.

How to become an ML research assistant?

To become an ML research assistant, candidates typically need a strong background in computer science, mathematics, or related fields, along with programming skills in languages like Python and experience with machine learning frameworks such as TensorFlow or PyTorch. A relevant bachelor's degree is often required, and advanced roles may require a master's or PhD. Gaining research experience through internships, projects, or academic work can improve prospects.
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Ml Research Assistant jobs near you
Infographic showing various Ml Research Assistant job openings in the United States as of August 2026, with employment types broken down into 2% As Needed, 75% Full Time, 20% Part Time, 1% Temporary, and 2% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution, with an average salary of $45,571 per year, or $21.9 per hour.

ML Validation Engineer - Early Career

General Motors

Sunnyvale, CA • On-site

Full-time

Re-posted 10 days ago

General Motors rating

8.2

Company rating: 8.2 out of 10

General Motors

Based on 306 frontline employees who took The Breakroom Quiz

7.4

Company rating compared to similar companies: 7.4 out of 10

Automakers average

Based on 6,290 frontline employees who took The Breakroom Quiz

Job description

Job Description
The ML Validation Research Engineer - Early Career will contribute to applied machine learning research focused on improving verification and validation of ML components used in robotics and autonomous driving systems. This role centers on simulation-based evaluation, performance monitoring and issue observability, uncertainty modeling, scenario coverage automation, and transforming advanced ML research into working prototypes that enhance the efficiency, accuracy, and coverage of ML system validation.
Key Responsibilities
  • Prototype research concepts into performant tools integrated into CI/CD and large-scale validation pipelines.
  • Develop AI-tools to improve performance monitoring and observability for autonomous vehicle stack
  • Advance ML research for open and and closed loop simulation validation.
  • Develop AI-centric automations to make issue triage and root cause analysis more scalable
  • Develop scenario generation, coverage-guided testing, and rare-event discovery tooling.
  • Create robust metrics, predictors, uncertainty and Out-of-Distribution detection methods for autonomy ML systems.
  • Evaluate deep learning modules across perception, prediction, and planning in realistic sensor and traffic simulation.
  • Improve behavioral coverage and hazard-aligned metrics used in release readiness decision making.
  • Collaborate with Simulation, Safety, Systems Engineering, and cross-functional partners.
  • Author technical documentation, white papers, and contribute to validation methodology standards.

Research Focus Areas
  • Scenario synthesis (diffusion models, generative models, counterfactuals)
  • Coverage-based and fuzzing-based evaluation for autonomy behavior
  • Uncertainty estimation, calibration, conformal prediction, OOD detection
  • Robustness testing and perturbation frameworks
  • Test suite prioritization, failure mining, and regression analysis

Required Qualifications
  • B.Sc or MS in ML, Robotics, Computer Science, or work related experience
  • Strong proficiency in Python, PyTorch/JAX/TensorFlow
  • Demonstrated ability to translate complex ML research ideas into functional prototypes
  • Experience integrating ML evaluation into CI/CD pipelines
  • Proven research impact through published work, internal tools, or patents
  • Strong communication skills and ability to collaborate cross-functionally

About GM
Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.
Why Join Us
We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.
Benefits Overview
From day one, we're looking out for your well-being-at work and at home-so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.
Non-Discrimination and Equal Employment Opportunities (U.S.)
General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.
All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.
We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.
Accommodations
General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, emailus or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

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About General Motors

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General Motors is a company with global scale and capabilities, headquartered in Detroit, Michigan, with employees around the world. The company employs over 165,000 people, serves six continents, operates across 22 time zones, and has a diverse workforce speaking 75 languages1. GM’s vision is to drive the world forward by pioneering innovations that move and connect people to what matters. The company is working towards an all-electric future with its new Ultium Platform and is pushing transportation options beyond our wildest imaginations with autonomous vehicles. GM is also committed to becoming the most inclusive company in the world.

Industry

Transportation equipment manufacturing

Company size

10,000+ Employees

Headquarters location

Detroit, MI, US

Year founded

1908

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