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Full Time Llm Researcher Jobs (NOW HIRING)

Traversal

AI Researcher

New York, NY · On-site

$160K - $300K/yr

LLM & Agent Research: Prototype and evaluate prompting strategies, reasoning workflows, and tool ... S. base salary range for this full-time, in-person role in New York is $160,000-$300,000, plus ...

NIO

LLM Algorithmic Optimization Engineer

San Jose, CA · On-site

$143K - $186K/yr

Conduct research and apply cutting-edge technologies to optimize Large Language Models (LLMs) and ... The US base salary range for this full-time position is $143,200.00 - $186,000.00. * Within the ...

Vast.ai Inc

AI Agent Researcher

San Francisco, CA · On-site

$160K - $320K/yr

Many are called, but few are chosen. * Full-Time * On-site at either our SF or LA offices Tech ... LLM assisted coding assessment (virtual 1 hour) * Meet and greet with coding assessment (on-site 2 ...

NIO

LLM Algorithmic Optimization Engineer

San Jose, CA · On-site

$143K - $186K/yr

Conduct research and apply cutting-edge technologies to optimize Large Language Models (LLMs) and ... The US base salary range for this full-time position is $143,200.00 - $186,000.00. * Within the ...

Apollo Research

AI Security Researcher

San Francisco, CA · On-site

$214K - $280K/yr

Experience with AI/ML systems security or LLM security. * Detection engineering, SOC, or incident ... Time Allocation: Full-time * Location: This is an in-person role working out of our London or San ...

Bomnin Chevrolet Dadeland

Sr. AI/ML Engineer (LLM)

Miami, FL · On-site

$99K - $137K/yr

Role Description This is a full-time, on-site role located in Miami, FL, for a Senior AI/ML ... Research and evaluate new technologies and methodologies in the LLM space to continuously improve ...

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Full Time Llm Researcher information

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$30K

$113.1K

$164.5K

How much do full time llm researcher jobs pay per year?

As of Sep 5, 2026, the average yearly pay for full time llm 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 does a full time LLM researcher do?

A Full Time LLM Researcher studies and develops large language models (LLMs), such as those used in artificial intelligence and natural language processing applications. Their work often involves designing experiments, training models on large datasets, evaluating model performance, and publishing research findings. They may also collaborate with engineers and data scientists to implement and optimize LLMs for real-world applications. This role typically requires strong programming skills, a background in machine learning, and expertise in natural language processing.

What are the key skills and qualifications needed to thrive as a full time LLM researcher?

To thrive as a Full Time LLM Researcher, you need a deep understanding of machine learning, natural language processing, and large language model architectures, often supported by an advanced degree in computer science or a related field. Proficiency with Python, deep learning frameworks (like PyTorch or TensorFlow), and experience using large-scale compute resources are typically required. Strong analytical thinking, problem-solving abilities, and clear communication help researchers articulate findings and collaborate effectively. These skills ensure high-impact research, innovative model development, and effective integration of new technologies into real-world applications.

What are some common challenges full time LLM researchers face when collaborating with cross-functional teams?

Full Time LLM Researchers often collaborate with engineers, data scientists, and product managers to deploy and refine language models. A common challenge is communicating complex research findings to non-experts, ensuring alignment between research goals and product requirements. Balancing experimental innovation with practical constraints, such as computational resources and project deadlines, can also be demanding. Effective collaboration requires adaptability, strong communication skills, and the ability to translate theoretical advances into applied solutions.

What is the difference between Full Time Llm Researcher vs Part Time Llm Researcher?

AspectFull Time Llm ResearcherPart Time Llm Researcher
Work HoursTypically 35-40 hours per weekLess than 20 hours per week
Employment StatusFull-time employmentPart-time employment
CredentialsUsually requires an LLM degree, relevant research experienceSame as full-time, but may have more flexible qualifications
Work EnvironmentResearch institutions, law firms, universitiesSimilar environments, with flexible scheduling

Full Time Llm Researchers work full-time hours, often with more responsibilities and consistent schedules, while Part Time Llm Researchers have flexible hours with potentially fewer responsibilities. Both roles typically require an LLM degree and involve research in legal fields, but the full-time position offers more stability and engagement.

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Full Time Llm Researcher jobs near you
Infographic showing various Full Time Llm Researcher job openings in the United States as of August 2026, with employment types broken down into 96% Full Time, 1% Part Time, and 3% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $113,102 per year, or $54.4 per hour.

Test Engineer-AI/LLM

OPPO US Research Center

Palo Alto, CA • On-site

Full-time

Re-posted 12 days ago

Job description

OPPO US Research Center is seeking a full-time meticulous and innovative AI/LLM Test Engineer to join our cutting-edge AI team. In this critical role, you will evaluate the performance, reliability, and safety of Large Language Models (LLMs) in real-world product scenarios and test end-to-end generative AI solutions. Your work will directly shape how users experience AI-powered features by ensuring robustness, accuracy, and alignment with product goals. This is a unique opportunity to pioneer testing methodologies for next-generation AI systems at the forefront of technology.
We are also seeking a Contractor based LLM Evaluation & QA Engineer to support the testing and validation of large language model (LLM)-powered applications. You will help implement test strategies, execute evaluation workflows, and assist in model performance validation across diverse generative AI use cases.
This contract role is ideal for someone with hands-on experience in AI/ML evaluation, QA engineering, or data analysis who wants to deepen their exposure to generative AI systems.
Requirements
Full-time position requirement:
Core Testing & Evaluation
  • Design and execute performance tests for LLMs across diverse product use cases (e.g., chatbots, content generation etc.).
  • Develop automated test frameworks to evaluate LLM outputs for accuracy, bias, safety, and coherence.
  • Conduct end-to-end testing of integrated generative AI solutions, including APIs, data pipelines, and user interfaces.

Optimization & Validation
  • Collaborate with ML engineers to validate fine-tuned models and optimize prompts for target scenarios.
  • Analyze model failures, edge cases, and adversarial inputs to identify risks and improvement areas.
  • Benchmark LLM performance against industry standards and product-specific KPIs.

Collaboration & Quality Assurance
  • Partner with product, engineering, and research teams to define test requirements and acceptance criteria.
  • Document defects, performance metrics, and test results to drive data-driven improvements.
  • Advocate for AI ethics and safety through rigorous testing of fairness, bias mitigation, and content moderation.

Innovation & Tooling
  • Build scalable tools for synthetic test data generation, prompt variation testing, and automated evaluation workflows.
  • Stay current with advancements in generative AI testing, including red-teaming techniques and evaluation frameworks (e.g., HELM, Dynabench).
  • Propose novel testing strategies for emerging challenges (e.g., hallucinations, context drift).

Basic Qualifications:
  • Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field, or equivalent practical experience.
  • 1+ years of experience in software testing, data science, or ML validation, with exposure to AI/ML systems.
  • Proficiency in Python and testing frameworks (e.g., PyTest, Selenium).
  • Hands-on experience evaluating LLMs in production environments (e.g., GPT, Claude, Llama, Gemini).
  • Strong analytical skills for dissecting model behavior, statistical performance, and failure modes.
  • Familiarity with cloud platforms (GCP, Azure, or AWS) and MLOps tooling (e.g., MLflow, Weights & Biases).
  • Experience with version control (Git) and agile development methodologies.

Preferred Qualifications:
  • Master's degree in AI, Machine Learning, or a related field.
  • Expertise in prompt engineering, LLM fine-tuning (e.g., LoRA, RLHF), or optimization techniques.
  • Experience with automated evaluation tools (e.g., LangChain, TruLens) or LLM-specific test suites.
  • Knowledge of data pipelines, SQL/NoSQL databases, and API testing (e.g., Postman).
  • Background in statistics, quantitative analysis, or data visualization for test insights.
  • Contributions to AI safety/ethics initiatives or open-source LLM evaluation projects.
  • Experience testing mobile-integrated AI solutions (Android/iOS).

Contractor position requirements:
Testing & Evaluation Support:
  • Execute pre-defined performance tests for LLMs across various tasks (e.g., summarization, Q&A, chatbot flows).
  • Run scripted evaluations to assess outputs for factuality, coherence, and safety.
  • Perform manual and automated test execution on APIs and LLM-integrated user interfaces.

Prompt & model validation:
  • Assist ML engineers in evaluating prompt variations and prompt-tuning outcomes.
  • Log and analyze failure cases, anomalies, and edge cases based on provided guidelines.

Collabration & Documentation
  • Work with QA leads, product managers, and ML engineers to understand test goals and criteria.
  • Report defects, compile evaluation summaries, and maintain testing logs.

Tooling & Antomation:
  • Use existing internal tools or frameworks to automate test runs and result collection.
  • Contribute to prompt generation, input templating, or result tagging processes.

Basic Qualifications:
  • Bachelor's degree or equivalent work experience in a technical field (e.g., Computer Science, Engineering, Data Science).
  • 6+ months experience in software QA, data labeling, LLM evaluation, or ML testing projects.
  • Basic Python proficiency, especially for data processing and automation tasks.
  • Familiarity with LLMs (e.g., GPT, Claude, Gemini) and prompt-based outputs.
  • Comfortable working with tools like Jupyter, Postman, or testing dashboards.
  • Detail-oriented with good documentation habits.

Contractor Details:
  • Duration: Long term
  • Rate: Commensurate with experience
  • Conversion Opportunity: High-performing contractors may be considered for full-time roles

Benefits
OPPO is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
The US base salary range for this full-time position is $100,000-$200,000 + bonus + long term incentives benefits. Our salary ranges are determined by role, level, and location.

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