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Technical > AI/ML Automation Specialist

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Short Description:

An AI/ML Automation Specialist is responsible for designing, developing, and implementing automation solutions using artificial intelligence and machine learning technologies. They build and optimize models to streamline business processes, improve efficiency, and enable data-driven decision-making. The specialist collaborates with data scientists, engineers, and business teams to integrate AI/ML solutions into existing systems and workflows. They also monitor performance, fine-tune algorithms, and ensure automation systems operate securely and effectively. Strong programming, analytical, and problem-solving skills are essential for success in this role.

Duties / Responsibilities:

  • Design, develop, and deploy automated machine learning (ML) workflows to streamline model training and deployment processes
  • Integrate AI/ML models into production environments using automation tools and frameworks such as Airflow, Kubeflow, or MLflow
  • Build and maintain pipelines for data ingestion, preprocessing, and feature engineering to support continuous learning systems
  • Collaborate with data scientists and engineers to optimize model performance and automate retraining processes
  • Implement monitoring systems to track model accuracy, drift, and performance in real time
  • Automate testing, validation, and deployment procedures for AI/ML solutions to ensure reliability and scalability
  • Maintain version control and reproducibility of models, datasets, and code using Git and MLOps best practices
  • Troubleshoot automation issues, perform root cause analysis, and propose improvements to AI infrastructure
  • Ensure compliance with data governance, security, and ethical AI guidelines throughout the automation lifecycle
  • Document technical processes, system configurations, and operational workflows for ongoing maintenance and audits

Skills / Requirements / Qualifications

  • Education: Bachelor’s or Master’s degree in Computer Science, Data Engineering, Artificial Intelligence, or a related technical field
  • Programming Skills: Proficiency in Python, R, or Java, with experience in ML libraries such as TensorFlow, PyTorch, or Scikit-learn
  • Automation Tools: Hands-on experience with MLOps platforms and workflow orchestration tools like Airflow, Kubeflow, or Jenkins
  • Cloud Expertise: Familiarity with cloud environments (AWS, Azure, or GCP) and their AI/ML services
  • Data Engineering: Strong understanding of ETL processes, APIs, and data pipeline automation
  • Analytical Thinking: Ability to identify automation opportunities and improve efficiency within AI/ML systems
  • Version Control & CI/CD: Knowledge of DevOps practices, Git, and continuous integration/continuous deployment (CI/CD) pipelines
  • Collaboration: Strong communication and teamwork skills to work effectively with data scientists, software engineers, and IT teams

Job Zones

  • Title: Job Zone Five Extensive Preparation Needed
  • Education: Most of these occupations require graduate school. For example, they may require a master's degree, and some require a Ph.D., M.D., or J.D. (law degree).
  • Related Experience: Extensive skills, knowledge, and experience are needed for these occupations. Many require more than five years of experience. 
  • Job Training: Employees may need some on-the-job training, but most of these occupations assume that the person will already have the required skills, knowledge, work-related experience, or training.
  • Job Zone Examples: These occupations often involve coordinating, training, supervising, or managing the activities of others to accomplish goals. Very advanced communication and organizational skills are required. 
  • Specific Vocational Preparation in years: 4-7 years preparation (8.0 and above)

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