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 strong 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 ​ • 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, and other stakeholders to build scalable and reliable AI/ML solutions. Requirements • Strong programming experience in Python. • Hands-on experience with LLM fine-tuning, particularly SFT and DPO. • Strong knowledge of Hugging Face Transformers, Datasets, and PEFT. • Experience working with AWS GPU/EC2 and SageMaker for ML workloads. • Strong understanding of MLOps, ML CI/CD, and model lifecycle management. • Experience with LLM model serving and production deployment. • Experience building training data preparation and processing pipelines. • Knowledge of model evaluation, benchmarking, and performance optimization. • Hands-on experience with model quantization. • ​Experience implementing A/B, Canary, and Shadow-mode deployments Benefits • Comprehensive Medical Coverage: Health insurance of INR 7.0 Lakhs for you and your family (up to 6 members), ensuring complete peace of mind. • Robust Protection Plans: Group Personal Accident Insurance and Group Term Life Insurance to safeguard you and your loved ones. • Retirement Benefits: PF and Gratuity provided as per standard government regulations. • Flexible Work Options: Enjoy hybrid work arrangements & flexible working hours • Generous Leave Policy: 21 days of annual leave, in addition to 10 company-declared holidays. • Employee Well-being Spaces: Access to a dedicated break-out area with round-the-clock refreshments for relaxation and rejuvenation.