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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - **Company:** Lyntris Inc. - **Location:** United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Automated Storage and Retrieval Systems, Cloud Engineering, Computational Linguistics, Continuous Integration, Monitoring of Systems, Python (Programming Language), Machine Learning, Tensorflow, Search Technologies, Pytorch, Large Language Models, Prompt Engineering, Question Answering, Information Technology, HuggingFace, Machine Learning Operations - **Published:** July 10, 2026 - **Apply:** https://ats.rippling.com/accelintjobboardtest/jobs/9c62ceb3-8438-4223-b526-ad2ac11c3bab ## About the Role * Bachelor's degree in Computer Science, Data Science, AI/Machine Learning, or a related technical field (or equivalent practical experience). * 2-4 years of experience building NLP pipelines for technical or structured document understanding, including extraction, summarization, semantic search, and question answering. * Hands-on experience with large language models (LLMs) and transformer architectures (BERT and successor models), including fine-tuning, prompt engineering, pipeline orchestration, and retrieval-augmented generation (RAG). * Experience processing complex technical documentation such as engineering manuals, specifications, technical artifacts, tables, and figures. * Strong proficiency in Python and modern machine learning frameworks, including PyTorch and Hugging Face Transformers. * Demonstrated experience converting unstructured text into structured, machine-actionable knowledge. * Currently holds an active U.S. national security clearance or be able to receive and maintain one. Preferred Qualifications (Not Required) * Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related field. * Experience deploying and maintaining production-scale NLP or LLM applications. * Familiarity with vector databases, embedding models, and semantic retrieval systems. * Experience with document parsing, OCR, layout-aware models, or multimodal document understanding. * Experience working with engineering, manufacturing, aerospace, defense, or other highly technical datasets. * Knowledge of MLOps practices, model monitoring, CI/CD pipelines, and cloud-based AI infrastructure. * Active-duty military experience. Physical Requirements * Prolonged periods sitting at a desk and working on a computer. * Must be able to lift up to 15 pounds at times. Clearance Requirements Some positions will require access to U.S. National Security information. Positions that require this access will be required to receive and maintain a U.S. government personnel security clearance (PCL). In order to qualify for this position, the candidate must be a US Citizen and either currently possess this National Security eligibility or be able to complete the investigation application process with a favorable determination and maintain that eligibility throughout their employment. ## Description Remote Hiring Remotely in United States Mid level Remote Hiring Remotely in United States Mid level Design and implement NLP and LLM-powered pipelines to extract, summarize, and semantically search technical documentation. Fine-tune transformer models, build RAG systems, convert unstructured documents into structured knowledge, optimize inference for production, and collaborate with engineers and SMEs to deploy document intelligence solutions. The summary above was generated by AI, We are seeking an experienced Machine Learning Engineer / NLP Engineer to develop intelligent document understanding solutions powered by modern natural language processing (NLP) and large language models (LLMs). In this role, you will build and optimize pipelines that transform complex technical documentation into structured, machine-actionable knowledge. You will work with transformer models, retrieval-augmented generation (RAG), and advanced document processing techniques to enable search, question answering, summarization, and information extraction across engineering and technical content., * Design, develop, and maintain NLP pipelines for technical and structured document understanding, including information extraction, summarization, semantic search, and question answering. * Build and optimize LLM-powered applications using transformer-based models, including fine-tuning, prompt engineering, and retrieval-augmented generation (RAG) architectures. * Process and analyze complex technical corpora, including engineering manuals, specifications, technical reports, drawings, tables, and figures. * Develop methods to convert unstructured and semi-structured documents into structured, machine-actionable knowledge for downstream applications. * Implement scalable machine learning solutions using Python and modern ML frameworks such as PyTorch and Hugging Face. * Evaluate model performance, improve accuracy, and optimize inference pipelines for production environments. * Collaborate with cross-functional teams, including software engineers, data scientists, and subject matter experts, to define requirements and deliver AI-enabled document intelligence solutions. * Performs other duties as assigned. ## Related Videos - [How AI Models Get Smarter](https://www.wearedevelopers.com/videos/1374-how-ai-models-get-smarter) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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