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AI/ML MLOps Engineer
DATAECONOMY
Hyderabad, IND
Full-time
Mid-Senior
Hybrid
Discovered 1 weeks ago
PythonLarge language model fine-tuningSupervised Fine-Tuning (SFT)Direct Preference Optimization (DPO)Hugging Face TransformersHugging Face Datasets
Free
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PythonLarge language model fine-tuningSupervised Fine-Tuning (SFT)
Role Overview
AI/ML MLOps Engineer focused on LLM fine-tuning and deployment.
The role covers data preparation, model fine-tuning, evaluation, deployment, monitoring, and continuous improvement across the ML lifecycle.
The position requires 5–8 years of experience and is based in Hyderabad.
Key Skills for This Role
PythonLarge language model fine-tuningSupervised Fine-Tuning (SFT)Direct Preference Optimization (DPO)Hugging Face TransformersHugging Face Datasets
Full Job Posting
Role overview
AI/ML MLOps Engineer focused on LLM fine-tuning and deployment.
The role covers data preparation, model fine-tuning, evaluation, deployment, monitoring, and continuous improvement across the ML lifecycle.
The position requires 5–8 years of experience and is based in Hyderabad.
Work arrangement
- Employment type is full-time with a hybrid work arrangement.
- Flexible working hours are available.
Key responsibilities
- Fine-tune LLMs using SFT and DPO.
- Develop training data pipelines for transformation, formatting, deduplication, filtering, and validation.
- Build model evaluation and benchmarking frameworks.
- Deploy and serve models using AWS GPU/EC2 and Amazon SageMaker.
- Optimize models through quantization, inference optimization, and resource utilization.
- Build MLOps and ML CI/CD pipelines across training, evaluation, packaging, deployment, and monitoring.
- Implement A/B, Canary, and Shadow-mode deployments, including automated promotion and rollback.
- Monitor model performance, latency, throughput, errors, GPU utilization, and resource consumption.
- Containerize workloads with Docker and manage them using Kubernetes and Amazon EKS.
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