Data scientist AI​/ML

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Job Title: Principal AI/ML Architect Data Science

Location: Onsite - Teaxs Locals

Experience: 12+ Years

We are seeking a highly experienced Principal AI/ML Architect with 12+ years of expertise in Data Science, Artificial Intelligence, Machine Learning, and Enterprise Analytics. The ideal candidate will lead the design, development, and deployment of scalable AI/ML solutions that drive business transformation. This role will be responsible for defining AI strategy, architecting enterprise-grade ML platforms, mentoring technical teams, and partnering with business stakeholders to deliver measurable outcomes through advanced analytics and intelligent automation.

• Define and drive enterprise AI/ML architecture strategy aligned with business objectives.
• Design scalable machine learning, deep learning, and generative AI solutions for large-scale production environments.
• Lead end-to-end AI lifecycle including data ingestion, feature engineering, model development, deployment, monitoring, and governance.
• Architect cloud-native AI platforms leveraging AWS, Azure, or Google Cloud Platform services.
• Develop MLOps frameworks for continuous integration, deployment, monitoring, and model governance.
• Design and implement predictive, prescriptive, and generative AI solutions across multiple business domains.
• Lead architecture reviews, technical design sessions, and AI governance initiatives.
• Collaborate with Data Engineers, Data Scientists, Product Owners, and Executive Leadership to define AI roadmaps.
• Establish best practices for model explainability, fairness, security, compliance, and responsible AI.
• Mentor and guide teams on advanced AI/ML methodologies and emerging technologies.

• 12+ years of experience in Data Science, Machine Learning, Artificial Intelligence, and Enterprise Data Platforms.
• Strong expertise in Python, SQL, R, and advanced statistical modeling.
• Extensive experience with Machine Learning, Deep Learning, NLP, Computer Vision, and Generative AI technologies.
• Hands‑on experience with LLMs, RAG architectures, AI Agents, Prompt Engineering, and Vector Databases.
• Expertise in MLOps frameworks including MLflow, Kubeflow, Sage Maker, Azure ML, or Vertex AI.
• Strong knowledge of distributed computing frameworks such as Spark and Databricks.
• Experience designing cloud-native AI solutions on AWS, Azure, or Google Cloud Platform.
• Deep understanding of data architecture, data governance, and AI security principles.
• Experience leading enterprise-scale AI transformation programs.