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.