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Remote Llm Trainer Jobs (NOW HIRING)

Bright Vision Technologies

LLM Prompt Specialist

$100K - $150K/yr

LLM Prompt Specialist - Remote Bright Vision Technologies is a technology consulting and software ... This commitment extends to all aspects of employment, including recruitment, hiring, training ...

eSimplicity

LLM Specialist

Columbia, MD · On-site +1

$93K - $100K/yr

Experience fine-tuning LLMs, applying parameter-efficient training methods (e.g., LoRA, PEFT), and ... Working Environment : eSimplicity supports a remote work environment operating within the Eastern ...

eSimplicity

LLM Specialist

Columbia, MD · On-site +1

$104K - $145K/yr

Working Environment : eSimplicity supports a remote work environment operating within the Eastern ... Occasional travel for training and project meetings. It is estimated to be less than 5% per year.

Horizon3.ai

Staff Attack Engineer, AI/LLM

Get to Know Us Horizon3 is a fast-growing, remote cybersecurity company dedicated to the mission of ... Target AI infrastructure (model serving, training pipelines, vector databases, GPU/MLOps tooling ...

Siemens Healthineers

AI LLM Engineer

Atlanta, GA · On-site +1

This role is designed to be onsite in Atlanta, Georgia with some remote/hybrid flexibility* What ... Develop Python based pipelines for model training, evaluation, and deployment * Apply prompt ...

Turing

Remote Private Equity Expert

Manhattan, NY · Remote

$100 - $200/hr

... training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM ... Evaluate LLM models on private equity topics such as LBO structuring, deal screening, operational ...

Alinia AI

Applied AI Research Intern

Demonstrated knowledge and practical experience in LLM training (Please note: this is a strict ... Hybrid or remote work, with preference for CET time zone * Collaborative culture : Small ...

Sigma Group

Tamil Translator (Remote) | Sigma AI

$45K - $58K/yr

... or LLM training * Strong attention to detail What will you do? Annotation - Audio/Video/Image ... remote , performed through an online platform available 24/7. This opportunity is offered for ...

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Remote Llm Trainer information

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$15

$36

$92

How much do remote llm trainer jobs pay per hour?

As of Sep 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 is a remote LLM trainer?

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 remote LLM trainer do?

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 are the key skills and qualifications needed to thrive as a remote LLM trainer?

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.

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.

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Remote Llm Trainer jobs near you
Infographic showing various Remote Llm Trainer job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 77% Full Time, 18% Part Time, 3% Contract, and 1% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $76,772 per year, or $36.9 per hour.

GenAI / LLM Engineer - Remote (should be able to work on PST time zones)

Remote

Rootshell Enterprise Technologies, Inc.
11 - 50 employees
Learn more about Rootshell Enterprise Technologies, Inc.external

Other

This job post has expired 2 days ago. Applications are no longer accepted.

Job description

GenAI/LLM Engineer
Remote (should be able to work on PST time zones)
Prefers local to bay area.
Implementing GenAI requires specialized expertise in large language models. Traditional data scientists often haven't had the opportunity to dive deep into the practical intricacies of LLMs-particularly advanced fine-tuning techniques, model compression strategies, memory optimization approaches, and specialized training workflows. This role requires a hands-on deep learning practitioner comfortable with modern frameworks and libraries specific to LLM development.
  • Enables domain-specific fine-tuning of models to Client unique utility context
  • Improves model performance while reducing computational costs through advanced optimization techniques
  • Creates Client-specific AI capabilities that address our unique operational challenges
  • Enables the CoE to move beyond generic AI tools to customized solutions that deliver higher business value

Key Responsibilities:
  • Implement and optimize advanced fine-tuning approaches (LoRA, PEFT, QLoRA) to adapt foundation models to Client domain
  • Develop systematic prompt engineering methodologies specific to utility operations, regulatory compliance, and technical documentation
  • Create reusable prompt templates and libraries to standardize interactions across multiple LLM applications and use cases
  • Implement prompt testing frameworks to quantitatively evaluate and iteratively improve prompt effectiveness
  • Establish prompt versioning systems and governance to maintain consistency and quality across applications
  • Apply model customization techniques like knowledge distillation, quantization, and pruning to reduce memory footprint and inference costs
  • Tackle memory constraints using techniques such as sharded data parallelism, GPU offloading, or CPU+GPU hybrid approaches
  • Build robust retrieval-augmented generation (RAG) pipelines with vector databases, embedding pipelines, and optimized chunking strategies
  • Design advanced prompting strategies including chain-of-thought reasoning, conversation orchestration, and agent-based approaches
  • Collaborate with the MLOps engineer to ensure models are efficiently deployed, monitored, and retrained as needed

Expected Skillset:
  • Deep Learning & NLP: Proficiency with PyTorch/TensorFlow, Hugging Face Transformers, DSPy, and advanced LLM training techniques
  • GPU/Hardware Knowledge: Experience with multi-GPU training, memory optimization, and parallelization strategies
  • LLMOps: Familiarity with workflows for maintaining LLM-based applications in production and monitoring model performance
  • Technical Adaptability: Ability to interpret research papers and implement emerging techniques (without necessarily requiring PhD-level mathematics)
  • Domain Adaptation: Skills in creating data pipelines for fine-tuning models with utility-specific content

Apply