Senior AIML Engineer

Job Title: Senior AI/ML Engineer

Experience: 10 Years

Location: Hyderabad India

Employment Type: Full-time

Role Summary:
We are looking for a highly experienced Senior AI/ML Engineer with strong hands-on expertise in designing
developing deploying and monitoring enterprise-scale AI/ML systems. The candidate must possess end-to-end
experience across the complete AI/ML lifecycle including model development deployment observability
governance optimization and production support.

Key Responsibilities:
Lead development and deployment of enterprise-scale AI/ML and Generative AI solutions.
Build and optimize end-to-end ML pipelines including experimentation deployment monitoring and retraining.
Develop scalable inference architectures vector search systems and RAG-based applications.
Implement observability monitoring governance and production support mechanisms for AI systems.
Drive model lifecycle management including versioning experimentation tracking and CI/CD automation.
Mentor engineering teams and establish AI/ML engineering best practices.
Collaborate with business stakeholders to identify and implement AI-driven solutions.
Optimize AI systems for scalability latency reliability and cost efficiency.
Lead development and deployment of enterprise-scale AI/ML and Generative AI solutions.
Build and optimize end-to-end ML pipelines including experimentation deployment monitoring and retraining.
Develop scalable inference architectures vector search systems and RAG-based applications.
Implement observability monitoring governance and production support mechanisms for AI systems.
Drive model lifecycle management including versioning experimentation tracking and CI/CD automation.
Mentor engineering teams and establish AI/ML engineering best practices.
Collaborate with business stakeholders to identify and implement AI-driven solutions.
Optimize AI systems for scalability latency reliability and cost efficiency.

Required Skills & Qualifications:
Strong hands-on experience in Artificial Intelligence Machine Learning and Generative AI systems.
Extensive experience in end-to-end ML lifecycle including data ingestion feature engineering model
development validation deployment monitoring and retraining.
Hands-on expertise with Python SQL APIs and ML frameworks such as Scikit-learn TensorFlow PyTorch
Hugging Face and LangChain.
Experience with Vector Databases RAG pipelines semantic search embeddings and LLM orchestration.
Strong expertise in MLOps tools including MLflow DVC Docker Kubernetes CI/CD pipelines and model
versioning.
Hands-on experience with observability logging tracing monitoring drift detection and model performance
tracking.
Experience building scalable cloud-native inference and AI deployment pipelines.
Strong understanding of distributed systems data engineering and scalable AI infrastructure.
Excellent stakeholder management and cross-functional collaboration skills.
Experience with Azure Cloud Stack is a plus