Position Details
About this role
Responsible for translating business needs into production AI/ML and LLM-powered systems, building end-to-end AI services to support operational workflows and deliver measurable value.
Key Responsibilities
- Build AI/ML services
- Deploy models in production
- Develop APIs and UI
- Containerize applications
- Optimize AI workflows
Technical Overview
Develops and deploys AI/ML models, APIs, and automation pipelines in cloud-native environments using Docker, Kubernetes, and CI/CD tools, with a focus on predictive analytics.
Ideal Candidate
The ideal candidate is a mid-level data scientist with experience in deploying AI/ML and LLM-powered systems, proficient in containerization and cloud deployment, capable of building scalable AI services that support business workflows.
Must-Have Skills
Nice-to-Have Skills
Tools & Platforms
Required Skills
Hard Skills
Soft Skills
Industry & Role
Keywords for Your Resume
Deal Breakers
Lack of experience with Docker or Kubernetes, No experience deploying AI/ML models, Inability to work with cloud-native environments
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