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

- Solid 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.

📌 AI/ML MLOps Engineer (Hyderabad)
🏢 Important Group
📍 Hyderabad