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Remote Large Language Model Llm Jobs (NOW HIRING)

AI Architect

OR ยท Remote

Artificial and Large Language Model Architect As an AI & LLM Architect , you will play a pivotal role in designing and implementing the technology architecture for advanced AI (including Large ...

... Large Language Model (LLM) solution to check coherence and consistency. Resource will also develop and modify existing models related to customer long term engagement and retention. This role will ...

The position is remote. This position requires the candidate to be able to obtain a Public Trust ... Strong understanding of large language model (LLM) capabilities, limitations, prompt engineering ...

The position is remote. This position requires the candidate to be able to obtain a Public Trust ... Strong understanding of large language model (LLM) capabilities, limitations, prompt engineering ...

LLM Specialist

Columbia, MD ยท On-site +1

$93K - $100K/yr

Experience developing and working with large language models (LLMs), transformer-based ... Working Environment : eSimplicity supports a remote work environment operating within the Eastern ...

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Remote Large Language Model Llm information

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How much do remote large language model llm jobs pay per hour?

As of Aug 24, 2026, the average hourly pay for remote large language model llm in the United States is $24.34, according to ZipRecruiter salary data. Most workers in this role earn between $18.99 and $29.09 per hour, depending on experience, location, and employer.

What is a remote large language model LLM?

A Remote Large Language Model (LLM) job involves working with advanced AI models, like GPT or similar, from a remote location. Professionals in these roles may develop, train, fine-tune, or implement large language models for various applications such as natural language processing, chatbots, or content generation. Remote LLM jobs can include positions like machine learning engineer, research scientist, or AI product manager. The work typically requires strong programming skills, experience with AI frameworks, and the ability to collaborate virtually with global teams.

What are the key skills and qualifications needed to thrive as a remote large language model LLM engineer?

To thrive as a Remote Large Language Model (LLM) Engineer, you need a strong background in computer science, machine learning, and natural language processing, typically supported by a relevant degree and experience with large-scale models. Proficiency with programming languages like Python, deep learning frameworks such as PyTorch or TensorFlow, and familiarity with cloud platforms and distributed systems are essential. Excellent problem-solving, communication, and collaboration skills are critical for remote teamwork and translating complex requirements into scalable solutions. These skills ensure the effective development, deployment, and maintenance of advanced language models in fast-evolving, distributed environments.

How does a remote large language model LLM engineer typically collaborate with cross-functional teams while working remotely?

Remote LLM Engineers often work closely with data scientists, product managers, and software engineers through virtual meetings, collaborative coding platforms, and shared documentation tools. Regular communication is key, with daily stand-ups or weekly syncs to align on project goals, update progress, and address challenges. They may also participate in code reviews, contribute to design discussions, and support model deployment efforts, all within a distributed team environment. This remote structure encourages self-motivation and proactive communication to ensure project success.

What is the difference between Remote Large Language Model Llm vs Data Scientist?

AspectRemote Large Language Model LlmData Scientist
Required CredentialsAdvanced degrees in AI, NLP, or related fields; experience with machine learning frameworksDegree in Data Science, Statistics, Computer Science, or related fields; strong analytical skills
Work EnvironmentPrimarily remote, focused on developing and fine-tuning language modelsRemote or on-site, analyzing data, building models, and generating insights
Employer & Industry UsageTech companies, AI research labs, startups working on NLP productsTech firms, finance, healthcare, marketing, and research organizations

While both roles involve data and machine learning, a Remote Large Language Model Llm specializes in developing and refining language models, whereas a Data Scientist focuses on analyzing data, building predictive models, and deriving insights across various domains.

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Infographic showing various Remote Large Language Model Llm job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 7% Part Time, and 4% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $50,625 per year, or $24.3 per hour.

LLM Application Engineer, Artificial Intelligence (AI) Required, Work From Home

Ginas Tech Jobs

San Francisco, CA โ€ข On-site, Remote

Full-time

Medical, Dental, Vision, PTO

Posted 12 days ago


Job description

Company Description
Job Description
LLM Application Engineer, Artificial Intelligence (AI) Required, Work From Home
As an LLM Application Engineer, you will build the intelligence layer that powers the AI experiences. You will work at the intersection of Large Language Models (LLMs), software engineering, and product designing agent workflows, improving model behavior, and turning Artificial Intelligence (AI) capabilities into reliable user experiences. You will own problems end-to-end, from understanding user needs, designing Agentic workflows, integrating models and tools, building evaluation systems and continuously improving AI behavior in production. This position is 100% Remote.
LLM Application Engineer Responsibilities:
- Build and ship LLM-powered applications and AI agent workflows.
- Design systems for reasoning, planning, memory, tool use and multi-step execution.
- Build reliable orchestration pipelines that turn probabilistic model outputs into predictable, observable, and safe actions.
- Integrate Large Language Models (LLMs) with APIs, databases, search, internal services, and external tools.
- Develop prompting, context engineering, structured outputs, tool-calling, and other techniques to improve model behavior.
- Build evaluation frameworks and datasets to measure AI quality, reliability, and regressions.
- Debug AI systems across the entire stack from model behavior and prompts to orchestration, backend services, and product UX.
- Optimize AI systems for quality, latency, and cost.
- Work closely with product and engineering teams to turn ambiguous product problems into working AI solutions.
- Establish production practices for observability, tracing, experimentation, evaluation, and continuous improvement.
LLM Application Engineer Outcomes:
- Artificial Intelligence (AI) features reach production quickly and deliver measurable user impact.
- LLM-powered workflows are reliable, scalable, observable, and maintainable.
- Artificial Intelligence (AI) quality improves through systematic evaluation, experimentation, and iteration.
- Artificial Intelligence (AI) workflows become increasingly predictable, efficient, and cost-effective.
- Complex AI capabilities are translated into simple, intuitive user experiences.
Qualifications
LLM Application Engineer Qualifications:
- Artificial Intelligence (AI) experience required.
- Strong software engineering fundamentals with experience building AI-powered applications.
- Hands-on experience with Large Language Models (LLMs), generative AI, or agent-based systems.
- Experience designing prompts, workflows, evaluations, or AI behavior.
- Ability to write clean, production-quality code.
- Comfortable working across abstraction layers from model to system to product.
- Strong problem-solving skills in ambiguous, fast-moving environments.
- Bias toward shipping, iteration, and continuous improvement.
- Tech Stack: Python, LLM APIs and model providers, including OpenAI-compatible APIs and open-weight models, Agent frameworks and orchestration systems, Vector databases and retrieval systems, Backend services, APIs, and distributed systems, and PyTorch / JAX.
Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.
Keywords: San Francisco CA Jobs, Agent Frameworks, AI, Artificial Intelligence, AI Agent Workflows, APIs, Application Engineer, Backend, Databases, Distributed Systems, JAX, LLM, Large Language Model, LLM APIs, OpenAI-Compatible APIs, Orchestration Systems, Python, PyTorch, UX, User Experience, Vector Databases, Work From Home, Remote, California Recruiters, IT Jobs, California Recruiting
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Additional Information
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