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Entry Level Ai Researcher Jobs (NOW HIRING)

XPENG

AI Intern - VLA Deployment

Santa Clara, CA · On-site

... R&D in AI, machine learning, and smart connectivity. The Mission: Vision-Language-Action (VLA ... We are looking for an entry-level engineer or intern to support the optimization and deployment of ...

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Entry Level Ai Researcher information

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$30K

$113.1K

$164.5K

How much do entry level ai researcher jobs pay per year?

As of Jul 24, 2026, the average yearly pay for entry level ai 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.

Are there any entry-level AI jobs?

Yes, entry-level AI researcher positions are available and typically require foundational knowledge in machine learning, programming skills in languages like Python, and familiarity with AI frameworks such as TensorFlow or PyTorch. These roles often involve assisting with data collection, model training, and experimentation under supervision, making them suitable for recent graduates or those new to the field.

What does an Entry Level AI Researcher do?

An Entry Level AI Researcher assists in developing and testing artificial intelligence models and algorithms. They typically work under the guidance of senior researchers, helping to collect and preprocess data, run experiments, and analyze results. Their tasks often include literature reviews, coding in languages like Python, and collaborating with teams to solve complex problems. This role provides a foundation for advancing to more specialized AI research positions.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior research scientists or AI executives, which offer compensation in that range including salary, bonuses, and stock options. Entry-level AI researchers usually earn significantly less, with salaries often starting from $70,000 to $120,000 depending on experience and location.

How do I get a job in AI with no experience?

Entry level AI researcher roles typically require foundational knowledge in programming, mathematics, and machine learning concepts. Gaining skills through online courses, tutorials, and building projects can demonstrate your abilities; internships or volunteering can also provide practical experience and improve your chances of securing a position.

How to get a job as an AI researcher?

To become an AI researcher, develop a strong foundation in computer science, mathematics, and machine learning through a relevant bachelor's or master's degree. Gain experience with programming languages like Python, work on AI projects or research, and stay updated with the latest advancements by reading academic papers and attending conferences. Building a portfolio of research or contributions to open-source AI projects can also improve job prospects.

What are the key skills and qualifications needed to thrive as an Entry Level AI Researcher, and why are they important?

To thrive as an Entry Level AI Researcher, a strong background in mathematics, programming (Python or similar), and machine learning concepts—often supported by a relevant degree—is essential. Familiarity with tools like TensorFlow, PyTorch, Jupyter Notebooks, and experience using version control systems such as Git are typically required. Analytical thinking, curiosity, and effective communication help researchers collaborate, learn quickly, and present findings clearly. These skills ensure the ability to contribute to innovative AI projects, solve complex problems, and work effectively within research teams.

What are the most common challenges faced by entry-level AI researchers when starting in the field?

Entry-level AI researchers often encounter challenges such as keeping up with the rapid pace of advancements in artificial intelligence, understanding complex mathematical concepts, and navigating large codebases or research papers. Adjusting to collaborative team dynamics, especially in interdisciplinary environments, can also be challenging. However, many organizations provide mentorship, regular knowledge-sharing sessions, and hands-on projects to help newcomers acclimate and grow their skills.

What is the difference between Entry Level Ai Researcher vs Data Scientist?

AspectEntry Level Ai ResearcherData Scientist
Required CredentialsBachelor's in CS, AI, or related field; some internshipsBachelor's or Master's in CS, Statistics, or related field; some internships
Work EnvironmentResearch labs, tech companies, academiaBusiness environments, tech firms, consulting
Industry UsageDeveloping AI models, research projectsAnalyzing data, building predictive models
Common Search IntentEntry level AI research roles, AI research jobsData analysis roles, data science jobs

Entry Level Ai Researcher and Data Scientist roles often require similar educational backgrounds and work in tech or research environments. However, AI Researchers focus more on developing and advancing AI algorithms, while Data Scientists analyze data to inform business decisions. Both roles are in high demand and serve different but overlapping functions within the tech industry.

More about Entry Level Ai Researcher jobs
What cities are hiring for Entry Level Ai Researcher jobs? Cities with the most Entry Level Ai Researcher job openings:
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What states have the most Entry Level Ai Researcher jobs? States with the most job openings for Entry Level Ai Researcher jobs include:
What job categories do people searching Entry Level Ai Researcher jobs look for? The top searched job categories for Entry Level Ai Researcher jobs are:
Entry Level Ai Researcher jobs near you
Infographic showing various Entry Level Ai Researcher job openings in the United States as of July 2026, with employment types broken down into 76% Full Time, 5% Temporary, and 19% Contract. Highlights an 95% In-person, and 5% Remote job distribution, with an average salary of $113,102 per year, or $54.4 per hour.

AI Intern - VLA Deployment

XPENG

Santa Clara, CA • On-site

Internship

Posted 20 days ago

Job description

XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&D in AI, machine learning, and smart connectivity.
The Mission: Vision-Language-Action (VLA) models and foundation models are becoming increasingly important in autonomous driving, but turning research models into real-time, production-ready systems on vehicle hardware remains a major challenge. We are looking for an entry-level engineer or intern to support the optimization and deployment of multimodal models onto vehicle-grade compute platforms. This role is a strong fit for candidates who are excited about deep learning systems, model deployment, and edge inference for real-world autonomous driving applications.
Key Responsibilities
  • Support model quantization and deployment efforts for large-scale multimodal models, including Transformers and vision-language models.
  • Assist with applying model optimization techniques such as post-training quantization, quantization-aware training, pruning, and related compression methods under guidance from senior engineers.
  • Work with research and platform teams to help improve model deployability and understand hardware and runtime constraints.
  • Contribute to deployment tools, test pipelines, and runtime modules in C++ and Python for autonomous driving systems.
  • Help analyze model performance, memory usage, latency, and numerical accuracy across different deployment targets.
  • Participate in debugging and performance tuning across the model, runtime, and system stack.
  • Support validation and testing workflows to ensure stable and reliable deployment in vehicle and simulation environments.

Basic Qualifications
  • BS, MS, or PhD in Computer Science, Electrical Engineering, Robotics, or a related field.
  • Strong programming skills in C++ and/or Python.
  • Familiarity with deep learning frameworks such as PyTorch.
  • Basic understanding of model inference, deployment, or optimization workflows using tools such as ONNX, TensorRT, or similar frameworks.
  • Exposure to model compression or quantization concepts such as INT8, FP16, or related approaches.
  • Interest in computer architecture, performance optimization, and edge or embedded systems.
  • Strong problem-solving skills and the ability to learn quickly in a fast-paced engineering environment.
  • Good communication skills and the ability to collaborate with cross-functional teams.

Preferred Qualifications
  • Internship, research, or project experience in deep learning model deployment, inference acceleration, or embedded AI.
  • Familiarity with Transformers, multimodal models, or foundation models.
  • Experience with CUDA or GPU programming.
  • Exposure to autonomous driving, robotics, or real-time systems.
  • Contributions to research projects, open-source repositories, or relevant course projects.

What do we provide:
  • A fun, supportive and engaging environment.
  • Infrastructures and computational resources to support your work.
  • Opportunity to work on cutting edge technologies with the top talents in the field.
  • Opportunity to make significant impact on the transportation revolution by the means of advancing autonomous driving.
  • Competitive compensation package.
  • Snacks, lunches, dinners, and fun activities.

We are an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons without regard to race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status or marital status or any other prescribed category set forth in federal or state regulations.

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