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Remote Llm Trainer Jobs in Washington (NOW HIRING)

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 ...

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Remote Llm Trainer information

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.

What are the most commonly searched types of Llm Trainer jobs in Washington?

The most popular types of Llm Trainer jobs in Washington are:

What job categories do people searching Remote Llm Trainer jobs in Washington look for?

The top searched job categories for Remote Llm Trainer jobs in Washington are:

What cities in Washington are hiring for Remote Llm Trainer jobs?

Cities in Washington with the most Remote Llm Trainer job openings:

Infographic showing various Remote Llm Trainer job openings in Washington as of August 2026, with employment types broken down into 72% Full Time, and 28% Contract. Highlights an 100% Remote job distribution.

LLM Specialist

eSimplicity

Columbia, MD • On-site, Remote

$93K - $100K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 18 days ago


Job description

Description

About Us: 

eSimplicity is a modern digital services company that partners with government agencies to improve the lives and protect the well-being of all Americans, from veterans and service members to children, families, and seniors. Our engineers, designers, and strategists cut through complexity to create intuitive products and services that equip federal agencies with solutions to courageously transform today for a better tomorrow. 


Responsibilities:  

The LLM Specialist will drive the design, development, and operationalization of advanced large-language-model capabilities across a cloud-based analytics ecosystem. This role leads innovation efforts around cutting-edge AI, owning the architecture and strategy for fine-tuning, retrieval-augmented generation (RAG), agentic frameworks, and domain-specific model adaptation. The specialist will guide the development of high-impact prototypes, oversee the evolution of scalable LLM pipelines, and ensure robust governance, security, and performance across all model implementations. Partnering with engineering, product, and data teams, this position provides technical leadership, evaluates emerging LLM technologies, sets best practices, and helps drive transformation through the practical, safe, and effective deployment of generative AI. 

Requirements

Required Qualifications:  

  • All candidates must pass public trust clearance through the U.S. Federal Government. This requires candidates to either be U.S. citizens or pass clearance through the Foreign National Government System which will require that candidates have lived within the United States for at least 3 out of the previous 5 years, have a valid and non-expired passport from their country of birth and appropriate VISA/work permit documentation.
  • Bachelor's Degree and 5+ years of previous systems engineering experience. 
  • Experience developing and working with large language models (LLMs), transformer-based architectures, and generative AI solutions. 
  • Experience fine-tuning LLMs, applying parameter-efficient training methods (e.g., LoRA, PEFT), and developing effective prompt engineering strategies. 
  • Experience designing, implementing, and optimizing Retrieval-Augmented Generation (RAG) solutions, including embeddings, retrieval workflows, vector databases, and search optimization. 
  • Hands-on experience with LLM development frameworks and orchestration tools such as LangChain, LlamaIndex, or similar technologies. 
  • Strong Python programming skills with experience building, testing, and deploying AI/ML applications. 
  • Experience working with distributed computing environments, GPU-accelerated workloads, or large-scale model training and inference. 
  • Experience designing, deploying, and supporting AI/ML solutions in cloud environments such as Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), or similar platforms. 
  • Knowledge of MLOps and LLMOps practices, including source control, CI/CD pipelines, automated testing, monitoring, performance optimization, and model governance. 
  • Ability to lead technical discussions, collaborate effectively with cross-functional teams, mentor team members, and communicate complex technical concepts to both technical and non-technical audiences. 

Desired Qualifications: 

  • Experience implementing multi-agent or agentic AI systems for task automation and reasoning.
  • Familiarity with LLM evaluation frameworks, structured benchmarking, or human-in-the-loop refinement methods (e.g., RLHF-style workflows).
  • Expertise with advanced retrieval techniques such as hybrid search, graph retrieval, or long-context optimization.
  • Experience optimizing model inference through quantization, model compression, or model distillation.
  • Background integrating LLM services with large-scale analytics environments (e.g., Databricks, Snowflake, Spark).
  • Strong skills in exploratory data analysis, feature engineering, and data modeling to support domain-specific LLM customization.
  • Experience developing innovative prototypes or POCs that leverage state-of-the-art generative AI approaches.
  • Exposure to emerging architectures such as mixture-of-experts models, long-context transformers, or experimental generative frameworks.


Working Environment:
eSimplicity supports a remote work environment operating within the Eastern time zone so we can work with and respond to our government clients. Expected hours are 9:00 AM to 5:00 PM Eastern unless otherwise directed by manager. 


Occasional travel for training and project meetings. It is estimated to be less than 5% per year. 


Benefits:
eSimplicity offers a comprehensive benefits package, including medical, dental, and vision coverage, 401(k) retirement benefits, paid time off, paid holidays, life and disability insurance, and additional wellness and employee support programs. Eligibility may vary based on employment status and applicable plan terms. 


Reasonable Accommodation:
eSimplicity is committed to providing reasonable accommodations to qualified individuals with disabilities during the application and hiring process. Applicants who need assistance or an accommodation should contact Human Resources.
 

Equal Employment Opportunity:
eSimplicity is an Equal Opportunity Employer, including disability and protected veteran status. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran status, disability, or any other legally protected status.