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Commission Large Language Model Llm Jobs (NOW HIRING)

Whiz Global LLC

ML engineer

Columbus, OH · On-site

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 ...

Jobtailor

Lead Data/AI Engineer

Atlanta, TX · On-site

$120 - $180/hr

Develop Generative AI and Large Language Model (LLM) solutions, including prompt engineering and Retrieval Augmented Generation (RAG) * Build APIs, integrations, automations, and microservices ...

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How much do commission large language model llm jobs pay per year?

As of Aug 24, 2026, the average yearly pay for commission large language model llm in the United States is $117,500.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,500.00 and $142,500.00 per year, depending on experience, location, and employer.

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

AspectCommission Large Language Model LlmData Scientist
Required credentialsAdvanced degrees in AI, NLP, or related fields; experience with machine learningDegree in Data Science, Statistics, Computer Science, or related fields; strong analytical skills
Work environmentResearch labs, AI companies, tech firms focusing on NLP and AI developmentCorporate, research institutions, or tech companies analyzing data and building models
Industry usageAI development, NLP applications, language modeling projectsData analysis, predictive modeling, business insights across industries

While both roles require expertise in data and machine learning, Commission Large Language Model Llm focuses on developing and fine-tuning language models, whereas Data Scientists analyze data to generate insights and build predictive models. The roles often overlap in skills but differ in primary responsibilities and work environments.

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Commission Large Language Model Llm jobs near you
Infographic showing various Commission Large Language Model Llm job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 9% Part Time, and 5% Contract. Highlights an 57% Physical, 1% Hybrid, and 42% Remote job distribution, with an average salary of $117,500 per year, or $56.5 per hour.

Software Engineer (Language Modeling), BS+12 yrs

Link, LLC

Columbia, MD • On-site

Full-time

Re-posted 5 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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