Dice is the leading career destination for tech experts at every stage of their careers. Our client, HonorVet Technologies, is seeking the following. Apply via Dice today!

Job: ML Engineers/Data Scientist
Location: Preferred Seattle and 100% Remote
Duration: 6+ Months Contract

Job Description:

We are seeking a highly skilled and motivated Natural Language Processing (NLP) Data Scientist with expertise in text classification, NLP preprocessing, prompt engineering, and Agentic AI. The ideal candidate will have a solid background in deep learning, large-scale NLP models, and the Hugging Face ecosystem, with hands-on experience fine-tuning BERT, GPT, and other transformer models.

You will be responsible for building cutting-edge NLP solutions, integrating with Large Language Models (LLMs), and applying prompt engineering techniques to optimize LLM performance. Experience working with cloud providers such as Azure OpenAI, AWS, and Google Cloud Platform is a plus.

Experience Range:

5 To 8 Years Of Relevant Experience

Primary Duties & Responsibilities:

Research, design, and implement NLP algorithms with a focus on fine-tuning LLMs (BERT, GPT, and variants) for various NLP tasks, including text classification, entity recognition, summarization, and information retrieval.
Develop and optimize preprocessing pipelines for NLP tasks, including tokenization, stemming, lemmatization, and vectorization.
Design and implement prompt engineering techniques to enhance LLM adaptability for different business applications.
Build and deploy Agentic AI solutions that integrate LLMs with multi-step reasoning, workflow automation, and real-time decision-making.
Develop custom fine-tuning strategies to improve model accuracy for domain-specific tasks.
Collaborate with cross-functional teams to integrate fine-tuned NLP and AI agent solutions into products and services.
Analyze and interpret experimental results, applying iterative model improvements based on real-world data.
Stay updated with the latest advancements in NLP, generative AI, and agent-based architectures, incorporating emerging methodologies into the workflow.
Work with distributed computing environments and cloud platforms such as Azure OpenAI, AWS, and Google Cloud Platform to deploy and scale NLP models.
Guide and mentor peers on LLM fine-tuning best practices, AI-driven automation, and high-performance NLP architectures.

Knowledge, Skills & Abilities:

Bachelor s or Master s degree in Computer Science, Data Science, AI, or a related field.
3-5 years of professional experience in NLP, AI, or Data Science roles.
Strong understanding of text classification, information extraction, document understanding, and sequence labeling.
Hands-on experience with Hugging Face Transformers, BERT, GPT, and other modern NLP models.
Proficiency in Python, TensorFlow, PyTorch, and relevant NLP libraries.
Solid experience in NLP data preprocessing techniques, including tokenization, lemmatization, and vectorization.
Expertise in prompt engineering techniques for improving LLM performance.
Familiarity with Agentic AI concepts, enabling AI agents to make independent decisions in complex workflows.
Strong knowledge of cloud computing platforms (Azure OpenAI, AWS, Google Cloud Platform) and containerized deployment (Docker, Kubernetes).
Experience with version control (Git), CI/CD, and software engineering best practices.
Ability to analyze large-scale datasets, derive insights, and optimize NLP model performance.