> Markdown version of [/jobs/ext/534945-data-scientist](https://www.wearedevelopers.com/jobs/ext/534945-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** LTM Inc - **Location:** Irving, TX, United States - **Salary:** $79,851.0 - $107,720.0 - **Contract:** Internship / Graduate position - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Encodings, Python (Programming Language), Machine Learning, Natural Language Processing, Tensorflow, Google Cloud, Pytorch, Large Language Models, Prompt Engineering, Generative AI, Scikit Learn, Optimization Algorithms, Machine Learning Operations, GPT - **Published:** June 11, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=e86ae3c2b2b74b36 ## About the Role Do you have experience in Natural language processing?, We are looking for a Data Scientist with strong experience in Generative AI Open AI LLM frameworks and Machine Learning to build scalable AI driven solutions for enterprise use cases, * Handson experience in Generative AI OpenAI LLM based applications * Experience with Vector Databases and embedding based retrieval * Strong expertise in Machine Learning ML algorithms and lifecycle * Programming in Python with libraries like scikit learn TensorFlow or PyTorch * Good to Have * Experience with NLP Transformers and RAG architectures * Exposure to ML Ops model deployment cloud platforms AWS, Azure, GCP * Knowledge of prompt engineering and LLM optimization techniques, Mandatory Skills : AI/Generative AI, Generative AI/Open AI/Vector DB, Industrial AI - Machine Learning (ML) ## Description * Design and develop Generative AI solutions using Open AI LLM models GPT embeddings etc * Implement RAG pipelines using Vector Databases FAISS Pinecone etc * Develop and deploy Machine Learning models for industrial business use cases * Work on end-to-end AI lifecycle data preparation model development evaluation and deployment * Collaborate with stakeholders to translate business requirements into AI solutions ## Related Videos - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [A Brief History of Data Storage](https://www.wearedevelopers.com/videos/974-a-brief-history-of-data-storage) - [How E.On productionizes its AI model & Implementation of Secure Generative AI.](https://www.wearedevelopers.com/videos/623-how-e-on-productionizes-its-ai-model-implementation-of-secure-generative-ai) - [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models) - [Enter the Brave New World of GenAI with Vector Search](https://www.wearedevelopers.com/videos/844-enter-the-brave-new-world-of-genai-with-vector-search) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts)