AI/ML Ops Engineer – AI Platform and Operations

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Written by AI from the job title and company, not by Advocate, so some details may not match this job. The employer's own page has the real description.

Position Overview

The AI/ML Ops Engineer – AI Platform and Operations at Advocate will be responsible for designing, implementing, and maintaining robust AI and machine learning operations, ensuring smooth transitions from research and development into production environments. This position requires a deep understanding of AI lifecycle management, including model deployment, monitoring, and optimization, while collaborating closely with data scientists, software engineers, and IT professionals to drive the integration of advanced AI technologies within the organization.

Job Responsibilities

• Design and implement AI/ML operations frameworks to streamline model deployment and monitoring.
• Collaborate with data scientists to integrate machine learning models into production environments.
• Automate processes for continuous integration and continuous delivery (CI/CD) of AI applications.
• Monitor and optimize model performance using monitoring tools and techniques.
• Develop and maintain documentation for AI systems, procedures, and best practices.
• Participate in troubleshooting and resolution of AI system-related issues.
• Support and train team members in AI/ML operations technologies and methodologies.
• Keep abreast of industry trends and advancements in AI/ML technologies.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• Minimum of 3 years of experience in AI/ML operations or a related technical role.
• Proficient in programming languages such as Python, Java, or Scala.
• Experience with cloud platforms (AWS, Azure, Google Cloud) and their AI/ML services.
• Familiarity with containerization technologies, such as Docker and Kubernetes.
• Strong problem-solving skills and ability to analyze complex systems.
• Excellent written and verbal communication skills.

Technologies & Tools

The AI/ML Ops Engineer will utilize a variety of technologies and tools to optimize AI and machine learning processes. This includes proficiency in cloud services (such as AWS Sagemaker and Azure ML), data orchestration tools (like Apache Airflow), containerization platforms (like Docker and Kubernetes), as well as CI/CD pipelines using tools like Jenkins or GitLab CI. The role also requires working with monitoring and performance analysis tools specialized for machine learning applications.

Ideal Candidates

The ideal candidate for the AI/ML Ops Engineer position will exhibit both technical expertise and an adaptive mindset, capable of thriving in a fast-paced environment. They should demonstrate a commitment to continuous learning and improvement, possessing strong analytical capabilities and keen attention to detail. Effective collaboration and communication skills are paramount, as this role involves working with diverse teams. Additionally, a passion for leveraging AI/ML technologies to achieve business objectives will distinguish the ideal candidate for this role.