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.