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Remote Llm Trainer Jobs (NOW HIRING)

Higharc

Research Engineer

Design end-to-end LLM training and fine-tuning pipelines tailored to construction domains ... Working at Higharc Higharc has been remote first since our founding in 2018. We offer flexible ...

Conexess Group

AI Principal Engineer (Remote)

... for training and fine-tuning AI models on healthcare financial data. • Lead distributed ... LLM orchestration frameworks and agent architectures. • Experience applying AI to structured ...

poolside

Member of Engineering (Scalability)

A basic understanding of LLM training and inference principles is required. We look for fast ... Fully remote work & flexible hours * 37 days/year of vacation & holidays * Health insurance ...

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How much do remote llm trainer jobs pay per hour?

As of Jul 13, 2026, the average hourly pay for remote llm trainer in the United States is $36.91, according to ZipRecruiter salary data. Most workers in this role earn between $19.23 and $52.88 per hour, depending on experience, location, and employer.

What are Remote LLM Trainers?

Remote LLM Trainers are professionals who work from any location to help train large language models (LLMs) by providing high-quality data, evaluating model outputs, and refining model behavior. They may annotate data, review AI-generated content, or design prompts and tasks to improve the model's performance. These roles are crucial in ensuring that LLMs become more accurate, safe, and useful across various applications. Remote LLM Trainers often have backgrounds in language, linguistics, data science, or related fields and rely on digital tools to collaborate with AI development teams.

What does a typical workday look like for a Remote LLM Trainer, and how do they collaborate with team members?

As a Remote LLM Trainer, your workday often involves creating, curating, and reviewing datasets, developing prompts, and evaluating large language model outputs for quality and safety. Much of your collaboration happens asynchronously through digital channels—such as project management tools, messaging platforms, and regular video meetings—with researchers, data scientists, and fellow trainers. You may also participate in feedback sessions to discuss model behavior and share insights on improving training methodologies. Adapting to rapidly evolving project requirements and maintaining clear communication are key to success in this distributed, fast-paced environment.

What is the difference between Remote Llm Trainer vs Data Scientist?

AspectRemote Llm TrainerData Scientist
Required CredentialsBackground in AI, NLP, or machine learning; often a degree in computer science or related fieldDegree in computer science, statistics, or related fields; often certifications in data analysis or machine learning
Work EnvironmentRemote, collaborative teams developing and fine-tuning language modelsRemote or on-site, analyzing data, building models, and deriving insights
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, consulting, and research organizations

While both roles involve working with data and machine learning, a Remote Llm Trainer specializes in training and refining language models, whereas a Data Scientist focuses on analyzing data, building predictive models, and deriving insights across various industries.

What are the key skills and qualifications needed to thrive as a Remote LLM Trainer, and why are they important?

To thrive as a Remote LLM Trainer, you need a deep understanding of machine learning, natural language processing, and large language models, typically supported by a degree in computer science or related fields. Experience with Python, deep learning frameworks like TensorFlow or PyTorch, and familiarity with annotation tools or data labeling platforms is essential. Strong communication, attention to detail, and the ability to work independently are standout soft skills in this role. These skills and qualities ensure accurate model training, effective collaboration with distributed teams, and the delivery of high-quality AI solutions.
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What cities are hiring for Remote Llm Trainer jobs? Cities with the most Remote Llm Trainer job openings:
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Remote Llm Trainer jobs near you
Infographic showing various Remote Llm Trainer job openings in the United States as of July 2026, with employment types broken down into 1% Locum Tenens, 4% As Needed, 89% Full Time, 2% Part Time, 2% Contract, and 2% Nights. Highlights an 77% Physical, 4% Hybrid, and 19% Remote job distribution, with an average salary of $76,772 per year, or $36.9 per hour.
NLP Architect Generative AI & Conversational Intelligence - Remote - 12+ Months Contract

NLP Architect Generative AI & Conversational Intelligence - Remote - 12+ Months Contract

TMS

Durham, NC • Remote

Contractor

Re-posted 10 days ago

Job description

Role: NLP Architect – Generative AI & Conversational Intelligence
Location: Remote
Duration: 12+ Months Contract
Experience Needed: 15+ Years
Visa: All Visas acceptable
About the Role:
We are seeking a Principal AI Architect – Generative AI & NLP to lead the design and deployment of next-generation AI platforms powering intelligent customer experiences. This role will drive innovation across LLM-based conversational AI, agent assist systems, and autonomous CX workflows, enabling scalable, secure, and human-like interactions across global enterprises. You will play a critical role in shaping the future of AI-driven contact center platforms, combining Generative AI, GraphRAG, RLHF, and multi-agent systems to deliver highly personalized, context-aware, and trustworthy customer interactions.
Required Qualifications: 15+ years of experience in AI/ML, NLP, or distributed systems
• 5+ years working with Generative AI and LLM-based systems
• Proven experience building production-grade AI platforms at scale
• Deep expertise in:
 1. GraphRAG architecture (not just RAG)
2. RLHF and alignment systems
3. Multi-agent AI systems
4. Distributed training and inference
• Strong programming skills in Python, Scala, or Java
• Experience with PyTorch, TensorFlow, Transformers
Key Responsibilities: