AI/ML Architect

Role: AI/ML Architect. Location: Plano, TX (Hybrid) Long Term Contract Designs and leads the development of artificial intelligence and machine learning solutions that align with business objectives. This role involves creating scalable AI/ML architectures, selecting appropriate algorithms and technologies, and guiding data science and engineering teams to deliver impactful AI-driven products. Key Responsibilities: • Design end-to-end AI and machine learning system architectures, including data pipelines, model development, deployment, and monitoring. • Collaborate with business stakeholders to understand requirements and translate them into technical AI/ML solutions. • Evaluate and select appropriate AI/ML frameworks, tools, and platforms. • Define best practices and standards for AI/ML model development, testing, and deployment. • Lead and mentor data scientists, ML engineers, and software developers in implementing AI solutions. • Ensure AI/ML systems are scalable, secure, and maintainable. • Oversee integration of AI/ML models with existing IT infrastructure and applications. • Monitor model performance and implement strategies for continuous improvement and retraining. Stay updated on the latest AI/ML research, tools, and industry trends to drive innovation. • Manage technical risks and troubleshoot complex AI/ML system issues. Required Skills and Qualifications: • Proven experience as an AI/ML Architect, Data Scientist, or Machine Learning Engineer. • Strong expertise in machine learning algorithms, deep learning, natural language processing, and computer vision. Proficiency with AI/ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, or similar. • Experience with cloud AI/ML services (AWS SageMaker, Google AI Platform, Azure ML). • Knowledge of data engineering, big data technologies, and data pipeline design. • Strong programming skills in Python, R, or Java. • Familiarity with containerization (Docker, Kubernetes) and CI/CD for ML workflows. Core AI/ML Technical Expertise: • These are non-negotiable for the role: • Strong knowledge of machine learning algorithms • Proven experience with deep learning Expertise in Natural Language Processing (NLP) • Expertise in Computer Vision Experience building end‑to‑end AI/ML models (data prep → training → deployment → monitoring) • AI/ML Tools, Frameworks & Libraries Candidates must have hands-on proficiency with: TensorFlow PyTorch Scikit-learn Other modern ML libraries as needed • Cloud AI/ML Platforms Experience with at least one major cloud ecosystem: AWS SageMaker Google AI Platform Azure ML (important if your company is MS‑driven) • Programming Skills Strong coding background in: Python (must-have) R or Java (secondary but required in the JD) 5. Data Engineering & Big Data Mandatory understanding of data workflows: Data pipeline design & orchestration Big data technologies (e.g., Spark, Hadoop, Kafka) Data preprocessing and feature engineering at scale • Architecture & System Design Clear ability to architect: Scalable AI/ML systems Model deployment pipelines Real-time or batch inference systems Integration with existing enterprise infrastructure