Top Natural Language Processing (NLP) Jobs in Denver & Boulder, CO

Own and evolve revenue calibration models tying CX interactions to revenue, design causal inference and experimentation frameworks, build LLM-powered classification/NLP pipelines, productionize models with Analytics Engineers, define segmentation and behavioral signals, and ensure statistical rigor for executive reporting and regulatory defensibility.

The Research Engineer will collaborate with scientists to develop and validate machine learning models for speech technologies, manage scalable training systems, and design tools for accessibility to non-technical users.

Design, build, and evaluate AI systems, focusing on natural language understanding and automation. Collaborate with teams to ensure production quality and performance metrics.

Remote entry-level NLP engineering role focused on building language processing pipelines. Responsibilities include fetching unstructured text/audio data, preparing data with NLTK/spaCy/Gensim/Librosa, and developing complex deep learning models (CNNs, RNNs, MLPs, autoencoders) in TensorFlow or PyTorch for classification, regression, clustering, anomaly detection and structured outputs.

Develop and deploy NLP pipelines: fetch and preprocess unstructured text/audio, build deep learning models (TensorFlow/PyTorch) for classification, regression, clustering, anomaly detection and structured outputs, work with embeddings, entity resolution, and collaborate with the data science team on product development.

Freelance PhD-level Brazilian Portuguese expert will create challenging, original literature and linguistics questions and model answers for AI training, breaking responses into cited factual segments. Work supports NLP training data; AI tools allowed only for research support. ~60 flexible hours over two months.

Architect and deploy AI-driven documentation and CCMS solutions for regulated life-science environments. Implement NLP/ML tools for content generation, translation, QA, and optimize translation memory and workflows across technical publications.

The Principal LLM Application Engineer will develop and optimize Large Language Models, lead projects, evaluate performance, and collaborate across teams to enhance AI capabilities in cybersecurity.

As an AI Conversation Designer, you'll create and optimize chatbot flows, analyze performance, and collaborate cross-functionally to enhance customer interactions using AI and NLP technologies.

Review and annotate Korean text and images (bounding boxes, structured questions, short summaries) following annotation guidelines to train AI systems. Work remote, 30-40 hrs/week for at least 3 months; on-the-job training provided.

Train and fine-tune large language models, build and maintain the full LLM stack and agentic pipelines, improve chat/agent algorithms, translate NLP research into roadmap, and collaborate with validation, content, and dataset teams to design experiments and measure model quality.