Senior AI Engineer in Mumbai 4-9 year(s) | MyCareernet | Hiring Now

Key Skills: LLM, Fast Api, AI/ML, Python, Docker, Agentic AI, CICD, Cloud (AWS / Azure / GCP) Roles and Responsibilities: Design, develop, and maintain backend services and APIs to support AI/ML applications at scale. Productionize ML and deep learning models with efficient, reliable, low-latency inference. Build scalable microservices and REST/gRPC APIs for deploying AI solutions in enterprise environments. Optimize model serving and inference performance using production deployment frameworks and runtimes. Implement MLOps practices including model versioning, monitoring, and automated deployments. Skills Required: Python and FastAPI for building backend services and AI/ML APIs. LLM and AI/ML experience, including prompt engineering and integrating LLMs into backend systems. Containerization with Docker to support consistent deployments. Production experience with inference pipelines and backend model serving. Good to Have: CI/CD practices for automated build, test, and deployment. Agentic AI experience and building agent workflows. Cloud experience with AWS, Azure, or GCP. Education: Bachelor's degree with at least 7 years of experience or Master's with at least 4 years of experience in Computer Science, Software Engineering, Data Science, or related fields. Key Skills: LLM, Fast Api, AI/ML, Python, Docker, Agentic AI, CICD, Cloud (AWS / Azure / GCP) Roles and Responsibilities: Design, develop, and maintain backend services and APIs to support AI/ML applications at scale. Productionize ML and deep learning models with efficient, reliable, low-latency inference. Build scalable microservices and REST/gRPC APIs for deploying AI solutions in enterprise environments. Optimize model serving and inference performance using production deployment frameworks and runtimes. Implement MLOps practices including model versioning, monitoring, and automated deployments. Skills Required: Python and FastAPI for building backend services and AI/ML APIs. LLM and AI/ML experience, including prompt engineering and integrating LLMs into backend systems. Containerization with Docker to support consistent deployments. Production experience with inference pipelines and backend model serving. Good to Have: CI/CD practices for automated build, test, and deployment. Agentic AI experience and building agent workflows. Cloud experience with AWS, Azure, or GCP. Education: Bachelor's degree with at least 7 years of experience or Master's with at least 4 years of experience in Computer Science, Software Engineering, Data Science, or related fields.