LLMs AI Jobs

Discover the latest remote and onsite LLMs AI roles across top active AI companies. Updated hourly.

Check out 81 new LLMs AI roles opportunities posted on The Homebase

AI Agent Evaluation Analyst (Freelance)

New
Top rated
Mindrift
Part-time
Full-time
Posted

The Analyst will review evaluation tasks and scenarios for logic, completeness, and realism while identifying inconsistencies and helping define gold standards for AI agents. They will closely collaborate with QA, writers, or developers to refine processes and ensure robust agent testing.

Undisclosed
HOUR

(USD)

Maybe global
Remote Solely
JSON
YAML
LLMs
Prompt Engineering
QA

AI Agent Evaluation Analyst (Freelance)

New
Top rated
Mindrift
Part-time
Full-time
Posted

Review evaluation tasks, scenarios, and policies for autonomous AI agents focused on logic, completeness, and realism. Annotate reasoning paths, identify inconsistencies, and help define expected behaviors while collaborating with QA, writers, or developers for scenario refinement.

Undisclosed
HOUR

(USD)

Maybe global
Remote Solely
JSON
YAML
LLMs
Prompt Engineering

AI Agent Evaluation Analyst (Freelance)

New
Top rated
Mindrift
Part-time
Full-time
Posted

The analyst will review evaluation tasks and scenarios for autonomous AI agents, identifying inconsistencies, missing assumptions, and unclear decision points. They will also help define expected behaviors and annotate reasoning paths to enhance agent evaluation frameworks.

Undisclosed
HOUR

(USD)

Maybe global
Remote Solely
JSON
YAML
LLMs
Prompt Engineering

AI Agent Evaluation Analyst (Freelance)

New
Top rated
Mindrift
Contractor
Full-time
Posted

You will review evaluation tasks and scenarios for autonomous AI agents to ensure logical consistency, completeness, and realism. Additional responsibilities include identifying inconsistencies, helping define gold standards for agent behavior, annotating reasoning paths, and suggesting refinements for better coverage of edge cases.

Undisclosed
HOUR

(USD)

Maybe global
Remote Solely
JSON
YAML
QA
LLMs
Prompt Engineering

AI Pilot Vibe Coding Assistant (Freelance)

New
Top rated
Mindrift
Part-time
Full-time
Posted

Vibe Coding Assistants collaborate with automation systems and AI-driven tools to solve complex technical tasks and deliver well-reasoned, clearly written outputs. Responsibilities include scripting, data processing, optimizing Python code, and enhancing AI output quality through direct collaboration with LLMs.

Undisclosed
HOUR

(USD)

Maybe global
Remote Solely
Python
LLMs
Data Analysis
Automation
Data Engineering

AI Pilot Vibe Coding Assistant (Freelance)

New
Top rated
Mindrift
Contractor
Full-time
Posted

Contribute to AI projects by collaborating with automation systems to deliver accurate, well-reasoned outputs. Tasks include coding, scripting, data processing, troubleshooting technical problems, and optimizing AI workflow outputs for real-world use.

Undisclosed
HOUR

(USD)

Maybe global
Remote Solely
Python
Data Analysis
Automation
LLMs

AI Pilot Vibe Coding Assistant (Freelance)

New
Top rated
Mindrift
Contractor
Full-time
Posted

Vibe Coding Assistants collaborate with AI automation systems and contribute well-reasoned, accurate, and clearly written outputs for diverse technical challenges. They script, automate, process data, troubleshoot technical problems, and help fine-tune AI outputs for quality and reliability.

Undisclosed
HOUR

(USD)

Maybe global
Remote Solely
Python
Data Analysis
LLMs
Scripting
Automation

AI Pilot Vibe Coding Assistant (Freelance)

New
Top rated
Mindrift
Contractor
Full-time
Posted

Vibe Coding Experts partner with automation systems, providing nuanced, creative input to ensure outputs are accurate and usable. They solve complex technical tasks, write efficient Python scripts, handle large datasets, and optimize AI-driven workflows to advance the capabilities of hybrid AI agents.

Undisclosed
HOUR

(USD)

Maybe global
Remote Solely
Python
LLMs
Data Analysis
Automation
JSON

AI Pilot Vibe Coding Assistant (Freelance)

New
Top rated
Mindrift
Contractor
Full-time
Posted

The Vibe Coding Assistant partners with AI systems to provide nuanced, well-reasoned, and accurate written outputs supported by credible sources. Responsibilities include solving complex tasks, writing Python scripts for automation and data processing, formatting outputs, and collaborating with AI workflows.

Undisclosed
HOUR

(USD)

Maybe global
Remote Solely
Python
LLMs
Data Analysis
Automation

AI Pilot Vibe Coding Assistant (Freelance)

New
Top rated
Mindrift
Part-time
Full-time
Posted

AI Pilot Vibe Coding Assistants collaborate with AI-driven systems to generate, refine, and submit accurate, well-structured outputs based on complex prompts. They handle coding, automation, data processing, troubleshooting technical issues, and improving AI output quality across diverse domains.

Undisclosed
HOUR

(USD)

Maybe global
Remote Solely
Python
LLMs
Data analysis
Automation
Data engineering

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[{"question":"What are LLMs AI jobs?","answer":"LLMs AI jobs involve working with large language models in various capacities. These roles include model development and optimization, application integration using techniques like retrieval-augmented generation (RAG), building agentic systems, data generation for fine-tuning, and code generation. Professionals in these positions typically create, deploy, and enhance AI systems that leverage advanced natural language processing capabilities."},{"question":"What roles commonly require LLMs skills?","answer":"Roles that commonly require large language model expertise include AI Researchers who work on model training and innovation, AI Software Engineers who build end-to-end solutions, Natural Language Processing Engineers who design and implement models, Applied AI Engineers who create generative AI solutions, Research Software Engineers focusing on computational efficiency, and LLM Trainers who generate high-quality data for fine-tuning."},{"question":"What skills are typically required alongside LLMs?","answer":"Skills typically paired with large language model expertise include programming (especially Python), prompt engineering, retrieval-augmented generation (RAG) techniques, API integration capabilities, data formatting knowledge (particularly JSON), and fine-tuning methodologies. Strong understanding of natural language processing principles, excellent communication skills, and domain-specific knowledge for particular industries are also valuable complementary skills."},{"question":"What experience level do LLMs AI jobs usually require?","answer":"Senior roles typically require 5+ years building production-grade machine learning systems with measurable impact. Entry-level positions exist for new graduates with strong programming foundations and NLP understanding. Most positions expect demonstrated experience with language models, API integration, or related technologies. Technical assessments often require minimum passing scores of 70-80% to qualify for these positions."},{"question":"What is the salary range for LLMs AI jobs?","answer":"The research provided doesn't include specific salary information for large language model jobs. Compensation typically varies based on role type (researcher, engineer, trainer), experience level, company size, location, and specific technical expertise. As a specialized AI skill, these positions generally command competitive salaries within the broader tech industry."},{"question":"Are LLMs AI jobs in demand?","answer":"Yes, large language model jobs are in high demand across multiple industries. Major technology companies like Google, Apple, and Moody's are actively recruiting for these positions. New job titles like prompt engineers and API integration experts have emerged specifically for this technology. The broad adoption of these models has created hiring needs at all experience levels, from new graduates to senior researchers."},{"question":"What is the difference between LLMs and Traditional Machine Learning in AI roles?","answer":"Large language models focus on generative AI and deep learning, working with text, code, and multimodal content to create new outputs. Traditional machine learning typically involves supervised/unsupervised algorithms like XGBoost that classify, predict, or cluster existing data. LLM roles emphasize prompt engineering, fine-tuning, and retrieval techniques, while traditional ML positions focus more on feature engineering, algorithm selection, and statistical analysis."}]