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Nlp Llm Engineer Jobs (NOW HIRING)

Consip S.P.A.

NY · On-site

... Language Processing Engineer è responsabile della progettazione, dello sviluppo e dell ... Sviluppo e addestramento modelli NLP e LLM * Ottimizzazione e validazione modelli NLP/LLM

Gap International

AI/LLM Engineer

Philadelphia, PA · On-site

As an AI/LLM Engineer, you will lead the design and implementation of advanced systems centered on ... Solid understanding of NLP concepts, transformer architectures, and evaluation metrics for LLM ...

Gap International

AI/LLM Engineer

Springfield, PA · On-site

As an AI/LLM Engineer, you will lead the design and implementation of advanced systems centered on ... Solid understanding of NLP concepts, transformer architectures, and evaluation metrics for LLM ...

Gap International

AI/LLM Engineer

Springfield, PA · On-site

As an AI/LLM Engineer, you will lead the design and implementation of advanced systems centered on ... Solid understanding of NLP concepts, transformer architectures, and evaluation metrics for LLM ...

Abbott Laboratories

Sr. Engineer, AI Platform

Madison, WI · On-site

$99K - $198K/yr

Lead the execution of ML, NLP, LLM deliverables in support of the AI strategies. * Collaborate closely with data scientists, machine learning engineers, and software engineers to ensure smooth ...

Yakamconsulting

Conduct data preprocessing, cleaning, and feature engineering to prepare text data for analysis ... Utilize NLP and LLM techniques to extract insights, sentiment analysis, entity recognition, and ...

Lincoln Financial

Lead Applied AI Engineer

Radnor, PA · On-site

$152K - $243K/yr

... NLP, LLM engineering, that directly aligns with the specific responsibilities for this position. 5+ years of experience in ML engineering, applied AI, NLP, LLM engineering, or a related field.

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Nlp Llm Engineer information

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$107.3K

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How much do nlp llm engineer jobs pay per year?

As of Sep 10, 2026, the average yearly pay for nlp llm engineer in the United States is $107,282.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is an NLP LLM engineer?

NLP LLM Engineers are specialized professionals who design, develop, and optimize natural language processing (NLP) systems, often using large language models (LLMs) like GPT, BERT, or similar architectures. They work on building AI applications that understand and generate human language, such as chatbots, language translators, or text summarizers. Their work typically involves fine-tuning pre-trained models, handling large datasets, and ensuring the models are efficient and accurate for specific tasks. These engineers need strong backgrounds in machine learning, programming, and linguistics to solve complex language problems. The role is in high demand due to the rapid growth of AI-powered language technologies.

What are the key skills and qualifications needed to thrive as an NLP LLM engineer?

To thrive as an NLP LLM Engineer, you need a strong background in computer science, machine learning, and natural language processing, often supported by a relevant degree and experience with language models. Proficiency with programming languages like Python, deep learning frameworks such as PyTorch or TensorFlow, and familiarity with libraries like Hugging Face Transformers is typically required. Strong problem-solving abilities, clear communication, and a collaborative mindset help distinguish top performers in this field. These skills and qualities are crucial for developing, fine-tuning, and deploying advanced language models that drive innovative AI applications.

What are some common challenges faced by NLP LLM engineers when deploying large language models in production environments?

NLP LLM Engineers often encounter challenges related to optimizing large language models for efficiency and scalability in production. These can include managing high computational costs, ensuring low-latency responses, and addressing data privacy concerns. Engineers must also collaborate closely with DevOps and data engineering teams to monitor performance, handle model updates, and ensure robust API integration. Staying current with rapid advancements in NLP research and adapting models to evolving business requirements are also key aspects of the role.

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Infographic showing various Nlp Llm Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 92% Full Time, 3% Part Time, and 4% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $107,282 per year, or $51.6 per hour.

LLM Engineer (GCP Preferred)

Atlanta, GA • Hybrid

Krest Global Solutions
See more jobs at Krest Global Solutionsexternal

$58 - $60/hr

Contractor

Re-posted 14 days ago

Job description

Job Title: LLM Engineer (GCP Preferred)

Work Time Zone: EST

Rate: $60/hour on 1099/C2C

Location: Atlanta, GA (Hybrid – 3 days on-site)

 

We are seeking a highly skilled and motivated LLM Engineer to design, build, and deploy advanced large language model (LLM) solutions that enhance procurement workflows and drive business automation. The ideal candidate will have a strong background in natural language processing, deep learning, and AI agent design, with hands-on experience fine-tuning foundation models and deploying them on Google Cloud Platform (GCP).

Key Responsibilities:

  • AI Agent Development
    Design and implement LLM-powered AI agents that optimize and automate procurement-related tasks, ensuring reliability, explainability, and business alignment.
  • Model Fine-Tuning & Optimization
    Fine-tune foundation models for domain-specific tasks, focusing on accuracy, latency, and scalability. Apply techniques such as parameter-efficient fine-tuning, prompt tuning, and adapter training.
  • Pipeline Engineering
    Build and maintain robust, production-grade pipelines for data ingestion, model training, evaluation, and inference using GCP services and open-source tools.
  • Prompt Engineering & RAG Implementation
    Leverage prompt engineering and Retrieval-Augmented Generation (RAG) to improve contextual accuracy and relevance of model outputs.
  • Stakeholder Collaboration
    Work closely with procurement experts, data engineers, and business leaders to gather requirements, align goals, and deliver impactful AI solutions.
  • Model Evaluation & Monitoring
    Establish evaluation metrics and monitoring tools to track model performance, accuracy, bias, and drift in real-world applications.
  • Integration & Deployment
    Collaborate with cross-functional teams to integrate LLMs into existing systems, leveraging LangChain, LangGraph, and GCP AI tools like Vertex AI for seamless deployment.

Must-Have Qualifications:

  • Master’s degree in mathematics, Physics, Computer Science,
  • 7 – 10 + years of experience in NLP, LLM development, or AI-driven automation.
  • Expertise in Python and deep learning frameworks such as PyTorch and TensorFlow.
  • Proficiency with LangChain, LangGraph, Hugging Face Transformers, and LLM model hubs.
  • Experience fine-tuning large-scale models and optimizing for real-time inference.
  • Solid understanding of vector databases, knowledge graphs, and embedding techniques.
  • Strong communication skills with the ability to translate complex AI concepts to non-technical stakeholders.
  • Proven experience working with Google Cloud Platform (GCP), especially with services like Vertex AI, BigQuery, and Cloud Functions.
  • Familiarity with multi-agent systems and reinforcement learning is a strong plus.