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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Data Scientist - Enterprise AI - **Company:** HP Inc - **Location:** Austin, TX, United States - **Experience:** Experienced - **Salary:** $130,700.0 - $205,200.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Github, Monitoring of Systems, Python (Programming Language), Machine Learning, Software Tools, SQL Databases, Cloud Platform System, Feature Engineering, GitHub Copilot, Large Language Models, Prompt Engineering, Apache Spark, Model Validation, Generative AI, Scikit Learn, Information Technology, Machine Learning Operations, Software Version Control, Data Pipelines, Databricks - **Published:** July 16, 2026 - **Apply:** https://dejobs.org/x/x/F15265E62F0749888D84A699F4181DB7/job/ ## About the Role The ideal candidate combines strong technical expertise in Large Language Models (LLMs), Generative AI, machine learning, and large-scale data analysis with the ability to work effectively in complex enterprise environments on multidisciplinary teams. Success in this role requires curiosity, initiative, strong communication skills, and a passion for turning emerging AI technologies into practical business solutions., * Bachelor's, Master's, or PhD in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, Engineering, Mathematics, or a related field. * 3+ years of experience developing AI, machine learning, and data science solutions. * Proficiency in Python and modern AI/ML libraries and frameworks. * Experience with model evaluation, experimentation, performance measurement, and validation methodologies. * Strong analytical skills with experience working with large-scale tabular datasets using SQL, Spark, Databricks, or similar technologies. * Ability to collaborate effectively in culturally diverse and distributed teams., * 5+ years of experience developing AI, machine learning, and data science solutions in an industry setting. * Experience developing AI solutions in cloud environments such as Azure, AWS, or GCP. * Proficiency using software development tools such as version control (e.g. Github) and AI-assisted development tools (e.g. Github Copilot) * Experience with Retrieval-Augmented Generation (RAG), prompt engineering, AI agents. * Familiarity with MLOps, model monitoring, observability, and enterprise AI governance concepts. * Experience communicating technical concepts to business stakeholders. * Experience working in highly collaborative, matrixed organizations. ## Description This position supports the Enterprise Operations Applied AI organization's mission of enabling AI-powered transformation through applied research, scalable solutions, responsible AI practices, and cross-functional collaboration., * Design, develop, and deploy AI-powered solutions leveraging Large Language Models (LLMs), Generative AI technologies, machine learning, and predictive analytics. * Develop data pipelines, feature engineering approaches, and analytical workflows that support AI solution development. * Research new AI methods, tools, and frameworks and determine their applicability to business problems across enterprise operations. * Design and execute experiments to evaluate model effectiveness, accuracy, robustness, and operational performance. * Analyze large-scale structured and semi-structured datasets to generate insights, build predictive models, and support operational decision-making. * Translate business requirements into technical approaches and clearly communicate AI concepts to both technical and non-technical audiences. * Support adoption of AI solutions through training, demonstrations, documentation, and stakeholder engagement. * Collaborate with distributed teams of engineers, data scientists, product owners, business leaders, and other technology organizations to deliver impactful solutions. * Contribute to AI best practices, reusable frameworks, and technical standards across the organization., * Demonstrates technical depth in LLMs, machine learning, and data science while maintaining a practical focus on implementation. * Communicates clearly with product managers, engineers, and operational teams. * Takes ownership of outcomes and proactively drives work forward without waiting for direction. * Continuously identifies opportunities to improve processes, solutions, and ways of working. Core Competencies * Applied AI & Machine Learning * Large Language Models (LLMs) & Generative AI * Data Science & Statistical Analysis * Enterprise Problem Solving * Experimentation & Model Evaluation * Communication & Storytelling * Cross-Functional Collaboration * Ownership & Accountability ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Inside the AI Revolution: How Microsoft is Empowering the World to Achieve More](https://www.wearedevelopers.com/videos/869-inside-the-ai-revolution-how-microsoft-is-empowering-the-world-to-achieve-more) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) ## Related Articles - [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) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Got AI ideas but no money? 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