AI​/ML Architect

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.

• Hybrid:
  In office/remote
• 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.

This position description identifies the responsibilities and tasks typically associated with the performance of the position. Other relevant essential functions may be required.

• Required Skills and Qualifications:
• 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 Tensor Flow, PyTorch, Scikit‑learn, or similar.
• Experience with cloud AI/ML services (AWS Sage Maker, 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.

Compensation can differ depending on factors including but not limited to the specific office location, role, skill set, education, and level of experience. UST provides a reasonable range of compensation for roles that may be hired in various U.S. markets as set forth below.

• Bachelor’s or master s degree in computer science, data science, artificial intelligence, or related field.
• Proficiency with AI/ML frameworks and libraries such as Tensor Flow, PyTorch, Scikit‑learn, or similar.
• Experience with cloud AI/ML services (AWS Sage Maker, Google AI Platform, Azure ML).
• Strong programming skills in Python, R, or Java.
• Familiarity with containerization (Docker, Kubernetes) and CI/CD for ML workflows.
• 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.
• Knowledge of data engineering, big data technologies, and data pipeline design.