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Large Language Model Llm Jobs (NOW HIRING)

Experience building and deploying Large Language Model (LLM) solutions. * Hands-on experience with Amazon Bedrock for LLM development is preferred. Responsibilities * Design, build, deploy, and ...

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Large Language Model Llm information

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

As of Aug 12, 2026, the average hourly pay for 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 are some common challenges faced by large language model llm engineers in their day-to-day work?

LLM Engineers often encounter challenges related to scaling models efficiently, optimizing performance on large and complex datasets, and ensuring the responsible use of AI technologies. Balancing the trade-offs between model accuracy, speed, and ethical considerations can be demanding, especially as real-world applications often require rapid iterations and rigorous testing. Additionally, staying updated with the latest research advancements and integrating new methods into production systems is an ongoing responsibility. Many engineers tackle these challenges by working closely with data scientists, researchers, and product teams in collaborative, agile environments.

What is a large language model llm?

A Large Language Model (LLM) job typically involves working with advanced AI models designed to understand and generate human-like text. Roles in this field may include research, data engineering, model fine-tuning, prompt engineering, or application development. Professionals in LLM jobs often work with machine learning algorithms, natural language processing (NLP), and large-scale datasets to enhance AI capabilities. These roles are common in AI-driven industries, including tech companies, research institutions, and startups. Strong programming skills, knowledge of deep learning frameworks, and expertise in NLP are often required.

What are the key skills and qualifications needed to thrive in the large language model llm position?

Excelling in the role of a Large Language Model (LLM) Engineer requires strong expertise in natural language processing, machine learning, and computer programming, often supported by an advanced degree in computer science or a related field. Familiarity with industry-standard frameworks like PyTorch or TensorFlow, as well as experience with cloud computing platforms and large-scale data management, is highly valued. Communication, creativity, and problem-solving are essential soft skills to effectively collaborate with cross-functional teams and innovate solutions. These skills ensure the development, deployment, and refinement of powerful language models that can address diverse business needs and technical challenges.

What jobs can I do with a large language model?

A large language model can be used in roles such as AI content developer, chatbot designer, or natural language processing specialist. These jobs involve tasks like training, fine-tuning models, creating AI-driven applications, and improving language understanding, often requiring skills in programming, data analysis, and machine learning tools.
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Infographic showing various Large Language Model Llm job openings in the United States as of August 2026, with employment types broken down into 56% Full Time, 6% Part Time, and 38% Contract. Highlights an 69% In-person, 6% Hybrid, and 25% Remote job distribution, with an average salary of $50,625 per year, or $24.3 per hour.

Software Engineer (Language Modeling), BS+12 yrs

Link, LLC

Columbia, MD

Full-time

Re-posted 23 days ago


Job description

Description: We are seeking a highly skilled and motivated Sr. LLM Engineer to join our team in driving the advancement of our Language Model infrastructure. As a key member of our AI/ML team, you will be responsible for the training, hosting, and optimization of Large Language Model (LLM) instances within our compute environment. The ideal candidate should possess a strong passion for pushing the boundaries of language technology, a deep understanding of LLM architectures, and the grit to tackle complex challenges head-on. This role requires a self-reliant individual with a drive to identify and fix inefficiencies, constantly striving to improve the codebase and optimize model performance. If you thrive in a fast-paced environment and have an unwavering commitment to delivering cutting-edge language solutions, this position is for you.
Responsibilities:
       Design, develop, and maintain the infrastructure for training, hosting, and serving LLM instances.
       Optimize model training pipelines to achieve high performance and resource efficiency.
       Implement and integrate state-of-the-art LLM architectures and techniques.
       Collaborate with cross-functional teams to understand business requirements and deliver impactful language solutions.
       Monitor and analyze model performance metrics, identifying areas for improvement and implementing optimizations.
       Develop and maintain documentation, best practices, and coding standards for LLM development and deployment.
       Stay up-to-date with the latest advancements in LLM research and industry trends, and incorporate them into our projects.
       Mentor and guide junior engineers, fostering a culture of continuous learning and knowledge sharing.
Skills Requirements:
       12+ years of experience in software engineering, with a focus on machine learning or natural language processing.
       Degree in Computer Science, Artificial Intelligence, or a related field.
       Strong expertise in deep learning frameworks such as TensorFlow, PyTorch, or MXNet.
       Proficiency in programming languages such as Python, C++, or Java.
       Solid understanding of LLM architectures, training techniques, and evaluation methodologies.
       Familiarity with cloud platforms (e.g., AWS, GCP) and their machine learning services.
       Knowledge of software engineering best practices, including version control, testing, and continuous integration/deployment.
       Excellent problem-solving and debugging skills.
       Strong communication and collaboration abilities to work effectively with cross-functional teams.
Nice to Haves:
       Advanced degree (Master's or Ph.D.) in Computer Science, Artificial Intelligence, or a related field.
       Proven track record of implementing and deploying large-scale LLM systems in production environments.
       Experience with distributed computing frameworks like Apache Spark or Hadoop.
       Experience with natural language understanding, generation, and dialogue systems.
       Familiarity with techniques such as transfer learning, few-shot learning, and reinforcement learning.
       Contributions to open-source projects or research publications in the field of LLMs.
       Experience with serving models using APIs and building scalable inference pipelines.
       Knowledge of DevOps practices and tools like Docker, Kubernetes, and Jenkins.
YOE Requirement: 12 yrs., B.S. in a technical discipline or 4 additional yrs. in place of B.S.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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