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Entry Level Artificial Intelligence Research Jobs

Kotoba

Artificial Intelligence Researcher

Sonoma, CA · On-site

Your work runs the full research lifecycle, from framing the question through distributed training, evaluation, and production deployment. ■ About Kotoba Kotoba is a generative AI company on a ...

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Entry Level Artificial Intelligence Research information

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How much do entry level artificial intelligence research jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for entry level artificial intelligence research in the United States is $14.60, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $15.14 per hour, depending on experience, location, and employer.

What is entry level artificial intelligence research?

An entry level artificial intelligence (AI) research position typically involves assisting in the development, implementation, and testing of AI models and algorithms under the supervision of more experienced researchers. Duties may include data collection and preprocessing, literature reviews, running experiments, and analyzing results. You may also collaborate with team members to write reports or papers and help improve existing AI systems. This role provides hands-on experience with machine learning frameworks, programming languages like Python, and exposure to real-world AI challenges.

What types of projects can I expect to work on as an entry level artificial intelligence researcher?

As an entry-level AI researcher, you'll typically support ongoing projects by assisting with data collection, cleaning, and analysis, as well as implementing and testing machine learning algorithms under the guidance of senior researchers. Your daily tasks may involve running experiments, monitoring model performance, and collaborating with cross-functional teams such as data engineers and software developers. This hands-on experience will help you build foundational skills and gain exposure to both theoretical and applied aspects of AI, setting the stage for future advancement.

What are the key skills and qualifications needed to thrive as an entry level artificial intelligence researcher?

To thrive as an Entry Level Artificial Intelligence Researcher, you need a solid background in computer science, mathematics, and programming, often demonstrated through a bachelor's or master's degree. Familiarity with tools such as Python, TensorFlow, PyTorch, and experience with data analysis and machine learning frameworks is typically required. Strong analytical thinking, curiosity, and effective communication skills set candidates apart in collaborative research environments. These skills ensure you can contribute to innovative AI projects, effectively interpret data, and work well within multidisciplinary teams.

What is the difference between Entry Level Artificial Intelligence Research vs Data Scientist?

AspectEntry Level Artificial Intelligence ResearchData 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
Employer & Industry UsageResearch-focused roles in AI developmentData analysis, modeling, and decision-making in various industries

Entry Level Artificial Intelligence Research and Data Scientist roles share similar educational backgrounds and work environments. However, AI research focuses more on developing new algorithms and models, while data scientists analyze data to inform business decisions. Both roles are essential in tech and research sectors, but their core responsibilities differ.

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Entry Level Artificial Intelligence Research jobs near you
Infographic showing various Entry Level Artificial Intelligence Research job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $30,372 per year, or $14.6 per hour.

Artificial Intelligence Researcher

Verita AI

San Francisco, CA • On-site

Other

Posted 8 days ago

Key responsibilities

  • Work with clients to understand their models, goals, and performance gaps.

  • Design evaluations for generative, multimodal, reasoning, tool-use, and agentic AI systems.

  • Analyze model outputs and benchmark results to identify and quantify failure modes.

Job description

Location: San Francisco

Employment Type: Full-time

Work Model: In-person


About Verita AI

Verita AI works with leading AI companies to identify model gaps and build the human data needed to improve model performance. Verita AI operates a vetted expert network that connects specialized professionals with leading AI laboratories and human-data companies. The network comprises more than 5,000 experts across finance, medicine, law, engineering, music, and other professional domains.


We recently raised a $6 million seed round led by Kindred Ventures.


About the Role

We are hiring an Applied AI Researcher to work directly with clients on model evaluation and data strategy.


You will evaluate model performance, identify failure modes, and recommend the datasets, rubrics, expert workflows, and quality controls needed to address them. You will then work with our operations and engineering teams to turn these recommendations into scalable data programs.


What You’ll Do

  • Work with clients to understand their models, goals, and performance gaps.
  • Design evaluations for generative, multimodal, reasoning, tool-use, and agentic AI systems.
  • Analyze model outputs and benchmark results to identify and quantify failure modes.
  • Recommend data solutions such as supervised fine-tuning data, preference data, expert demonstrations, critiques, and evaluation datasets.
  • Write client proposals covering the methodology, data design, quality controls, staffing, deliverables, and expected impact.
  • Create annotation guidelines, scoring rubrics, gold-standard tasks, and evaluator-training programs.
  • Design pilot studies and measure whether data interventions improve model performance.
  • Build quality systems using calibration tasks, blind review, adjudication, and expert scoring.
  • Work with operations and engineering teams to launch and scale data pipelines.
  • Present findings and recommendations to clients.


What We’re Looking For

  • Experience in applied AI research, machine learning, model evaluation, or data-centric AI.
  • Experience evaluating foundation models or generative AI systems.
  • Strong understanding of benchmark design, human evaluation, rubric development, and statistical analysis.
  • Ability to translate model failures into practical data solutions.
  • Strong Python skills and experience working with model APIs and structured datasets.
  • Familiarity with supervised fine-tuning, preference optimization, RLHF/RLAIF, reward modeling, synthetic data, or LLM-as-a-judge evaluation.
  • Strong technical writing and client communication skills.
  • Ability to independently structure and execute ambiguous research projects.


Nice to Have

  • Experience at an AI lab, foundation-model company, AI data company, or post-training team.
  • Experience designing expert-data or human-evaluation programs.
  • Experience evaluating multimodal, coding, agentic, or tool-use systems.
  • Publications at conferences such as NeurIPS, ICML, ICLR, ACL, or EMNLP.
  • Previous client-facing research, consulting, solutions engineering, or forward-deployed experience.
  • Public research, code, benchmarks, or evaluation frameworks.


Please make sure you have any relevant work samples, including model evaluations, benchmarks, error analyses, research, technical writing, or code repositories.


Apply