LLMOps & AI Platform Release Engineer
- Industry Type
- Medical, Healthcare, Diagnostics, Medical Devices
- Functional Area
- IT Information Technology Industry Medical, Healthcare, Diagnostics, Medical Devices
- Nationality
- Any
- Keywords
- Deployment Automation
Job Description
D4Insight in Abu Dhabi is looking for an AI Operations Engineer to build and lead the release process for enterprise AI platforms. The role involves managing production releases and applying best practices for Low-Level Machine Operations to ensure safe and scalable AI product deployments.
- Position
- LLMOps & AI Platform Release Engineer
- Company
- D4Insight
- Location
- Abu Dhabi, UAE
- Industry
- Medical, Healthcare, Diagnostics, Medical Devices
- Experience
- 1 to 20 years
Responsibilities
- Establish the operational foundation for enterprise-level AI platforms.
- Lead the production release discipline.
- Implement best practices for Low-Level Machine Operations (LLMOps).
- Ensure safe, repeated, and scalable release of AI products for application teams.
Requirements
- Strong background in automation.
- Experience with deployment practices.
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About the role: LLMOps & AI Platform Release Engineer
General information about this type of role, not from the employer. The employer's actual requirements may differ, so always check the job details above.
LLMOps & AI Platform Release Engineers manage the deployment and maintenance of AI and machine learning systems, particularly in medical and healthcare settings. They work to ensure that AI platforms operate smoothly and securely, often collaborating with software developers and data scientists in hospitals, research centers, or medical device companies.
What this role usually involves
- Deploy and release AI and machine learning models into production environments.
- Monitor and maintain AI platforms to ensure reliability and performance.
- Collaborate with development and data science teams to integrate new features and updates.
- Automate deployment processes and manage version control for AI models.
- Troubleshoot and resolve issues related to AI platform releases.
- Ensure compliance with industry standards and best practices for AI system deployment.
Skills employers usually look for
- Knowledge of machine learning operations (MLOps) and AI platform management.
- Experience with cloud services and containerization tools like Docker and Kubernetes.
- Strong scripting and automation skills using languages such as Python or Bash.
- Understanding of software development lifecycle and version control systems.
- Ability to work with cross-functional teams including data scientists and engineers.
- Problem-solving skills and attention to detail in system monitoring and troubleshooting.
Usual qualifications
- A degree in computer science, software engineering, or a related field is usually expected.
- Background or certification in machine learning operations or AI platform management is beneficial.
- Familiarity with cloud computing platforms and DevOps practices is often required.
- Experience or training in healthcare or medical technology environments can be an advantage.
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