Job Title: AI/ML MLOps Engineer – LLM Fine-Tuning & Deployment
Experience: 5–8 Years
Location: Hyderabad
Employment Type: Full-Time, Hybrid

We are looking for an experienced AI/ML MLOps Engineer with robust hands-on expertise in LLM fine-tuning, model deployment, AWS GPU infrastructure, and MLOps. The role involves fine-tuning and deploying self-hosted Large Language Models (LLMs), building training and evaluation pipelines, and implementing reliable production deployment and monitoring practices.The ideal candidate should have practical experience working across the complete ML lifecycle — data preparation, model fine-tuning, evaluation, deployment, monitoring, and continuous improvement.

Key Responsibilities
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Fine-tune Large Language Models using Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO).
Develop and maintain training data pipelines, including data transformation, formatting, deduplication, filtering, and quality validation.
Work extensively with the Hugging Face ecosystem, including Transformers, Datasets, and PEFT.




Build and automate model evaluation and benchmarking frameworks to assess model quality and performance.
Deploy and serve LLM models using AWS GPU/EC2 infrastructure and Amazon SageMaker.
Optimize models for production through model quantization, inference optimization, and resource utilization.
Build robust MLOps and ML CI/CD pipelines covering model training, evaluation, packaging, deployment, and monitoring.
Implement A/B testing, Canary, and Shadow-mode deployments for safely introducing new model versions into production.
Develop mechanisms for automated model promotion and rollback based on predefined performance and operational metrics.
Implement production monitoring for model performance, latency, throughput, errors, GPU utilization, and resource consumption.
Containerize ML workloads using Docker and deploy/manage them using Kubernetes/Amazon EKS.
Collaborate with Data Scientists, ML Engineers, DevOps teams, an

📌 AI/ML MLOps Engineer (Hyderabad)
🏢 DataEconomy
📍 Hyderabad