Role: AI/ML Architect
Location: Plano, TX (Hybrid)
Duration: 12+ Months
Requirements:
Job Description Position Overview:
An AI/ML Architect 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.
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.
Requirements:
• Bachelor’s or master’s degree in computer science, Data Science,
Artificial Intelligence, or related field.
• 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
• Years of Experience – 10 years Plus