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Entry Level Llm Researcher Jobs (NOW HIRING)

United Smart Tech

AI Engineer (Entry-Level)

Carrollton, TX · On-site

$20 - $23/hr

Research and apply new AI tools, libraries, and agent frameworks as they emerge * Collaborate with ... Familiarity with LLM APIs, prompt engineering, or agent frameworks * Exposure to cloud platforms or ...

United Smart Tech

AI Engineer (Entry-Level)

Carrollton, TX · On-site

$20 - $23/hr

Research and apply new AI tools, libraries, and agent frameworks as they emerge * Collaborate with ... Familiarity with LLM APIs, prompt engineering, or agent frameworks * Exposure to cloud platforms or ...

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Entry Level Llm Researcher information

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$30K

$113.1K

$164.5K

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

As of Sep 5, 2026, the average yearly pay for entry level 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 is an entry level LLM researcher?

An Entry Level LLM Researcher is someone who assists in the development and analysis of large language models (LLMs) such as GPT, BERT, or similar AI systems. These researchers typically work under the guidance of more experienced scientists to gather data, run experiments, and evaluate model performance. They may also contribute to literature reviews, help with dataset curation, and support the implementation of research prototypes. This role is ideal for individuals with a background in computer science, machine learning, or related fields who are looking to gain hands-on experience in state-of-the-art AI research.

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

To thrive as an Entry Level LLM Researcher, you need a solid background in computer science, mathematics, and machine learning, often supported by a relevant degree. Familiarity with programming languages (such as Python), deep learning frameworks (like PyTorch or TensorFlow), and version control systems is typically required. Critical thinking, curiosity, and the ability to collaborate effectively are important soft skills in this position. These skills and qualities are essential to contribute to cutting-edge research, solve complex problems, and work efficiently within research teams.

What are some common challenges faced by entry level LLM researchers when working on large language model projects?

Entry-level LLM researchers often encounter challenges such as understanding complex machine learning concepts, keeping pace with rapidly evolving research, and managing large datasets. They may also need to learn new frameworks and tools for model training and evaluation, as well as collaborate with more experienced researchers and engineers. Additionally, balancing independent research with team-driven goals and deadlines can require strong organizational and communication skills.

What is the difference between Entry Level Llm Researcher vs Legal Research Assistant?

AspectEntry Level Llm ResearcherLegal Research Assistant
Required CredentialsLLM degree or in progressTypically a bachelor's degree, some may have paralegal certification
Work EnvironmentAcademic, law firms, research institutionsLaw firms, corporate legal departments, government agencies
Employer & Industry UsageLegal research, policy analysis, academic projectsLegal support, case preparation, legal documentation

While both roles involve legal research, an Entry Level Llm Researcher usually holds an advanced law degree and focuses on in-depth legal analysis or academic projects. A Legal Research Assistant typically has a bachelor's degree and supports attorneys with case-related research and administrative tasks. The roles differ mainly in educational requirements and scope of responsibilities, but both are essential in legal and academic settings.

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Entry Level Llm Researcher jobs near you
Infographic showing various Entry Level Llm Researcher job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $113,102 per year, or $54.4 per hour.

Generative AI Researcher

Tata Consultancy Services

Warren, MI

Full-time

Re-posted 17 days ago

Tata Consultancy Services rating

6.5

Company rating: 6.5 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

176th of 226 rated it services

Job description

Job Summary:

We are seeking a highly skilled and creative Entry Level - Generative AI Engineer to apply state-of-the-art generative models to solve complex challenges in automotive engineering. This role focuses on creating intelligent agents that leverage generative capabilities for reasoning, planning, and executing complex tasks autonomously. The ideal candidate will bridge the gap between generative AI's creative potential and agentic AI's autonomous action, developing systems that can understand, reason, and act in dynamic environments.

Key Responsibilities

Integrated AI System Development:

Design and build AI agents that utilize large language models for reasoning and decision-making

Develop systems where generative AI components enable sophisticated planning and problem-solving

Create autonomous agents capable of using tools, APIs, and external systems through generative interfaces

Implement multi-agent systems where generative AI facilitates communication and collaboration

Generative AI Capabilities:

Fine-tune and optimize large language models for specific agentic tasks

Develop prompt engineering strategies for complex reasoning and chain-of-thought processes

Implement RAG (Retrieval-Augmented Generation) systems to enhance agent knowledge and context

Create generative models for code generation, content creation, and strategic planning within agent frameworks

Agent Architecture & Autonomy:

Build reflective agents that can critique and improve their own reasoning processes

Design goal-oriented systems that use generative AI for planning and adaptation

Implement memory architectures that allow agents to learn from experience and maintain context

Develop safety mechanisms and oversight for autonomous generative agents

Multi-Modal Agent Systems:

Integrate vision, language, and action capabilities within agent frameworks

Develop agents that can process and generate across multiple modalities (text, image, audio)

Create embodied agents that interact with digital and physical environments

Research & Innovation: Stay current with the latest academic research and open-source advancements in generative AI. Prototype new ideas and conduct experiments to validate their feasibility and impact.

Education: Ph.D in Computer Science, Electrical Engineering, Mechanical Engineering or related streams.

Technical Proficiency:

Experience with generative AI (LLMs, diffusion models, generative architectures)

Experience with agentic AI systems, reinforcement learning, or autonomous systems

Strong programming skills in Python and experience with AI/ML frameworks (PyTorch, TensorFlow)

Experience with LangChain, AutoGPT, Microsoft Autogen, or similar agent frameworks

Proficiency with transformer architectures and fine-tuning techniques

Deep understanding of prompt engineering, reasoning techniques, and LLM capabilities

Experience with RAG systems, vector databases, and knowledge retrieval

Knowledge of reinforcement learning, planning algorithms, and decision-making systems

Familiarity with multi-agent systems and emergent behavior

Ph.D

What Tata Consultancy Services employees say

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Benefits

Hours and flexibility

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