AI/ML MLOps Engineer

DATAECONOMY Inc; Hyderabad, Pune District; On-site; INR 2,000,000 - 3,200,000; Full time

Benefits offered by this job

Health insurance

Insurance protection

Hybrid work

Leave policy

Break area

PF & Gratuity

Job summary

DATAECONOMY Inc in Hyderabad is seeking an experienced AI/ML MLOps Engineer to lead fine-tuning of self-hosted LLMs and deploy them in production. You will build training and evaluation pipelines, optimize for performance, and implement robust MLOps practices across CI/CD, monitoring, and deployment. Hybrid work model with competitive benefits.

Candidates should have hands-on expertise across the full ML lifecycle and strong AWS SageMaker experience.

Qualifications

• Strong Python programming experience.
• Hands-on LLM fine-tuning with SFT and DPO.
• Experience with HuggingFace Transformers, Datasets, and PEFT.
• Experience 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.

Responsibilities

• Fine-tune Large Language Models using Supervised Fine-Tuning (SFT) and DirectPreference 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.

Skills

Python

LLM fine-tuning

HuggingFace Transformers

PEFT

AWS SageMaker

MLOps

Docker

Kubernetes

Tools

Docker

Kubernetes

Amazon EKS

Job description

Hyderabad/Pune, India | Posted on 08/31/2026

Experience: 5–8 Years

Employment Type: Full-Time, Hybrid

We are looking for an experienced AI/ML MLOps Engineer withstrong hands-on expertise in LLM fine-tuning, model deployment, AWS GPUinfrastructure, and MLOps. The role involves fine-tuning and deployingself-hosted Large Language Models (LLMs), building training and evaluationpipelines, and implementing reliable production deployment and monitoringpractices.The ideal candidate should have practical experience working across thecomplete ML lifecycle — data preparation, model fine-tuning, evaluation,deployment, monitoring, and continuous improvement.

Key Responsibilities

• Fine-tune LargeLanguage Models using Supervised Fine-Tuning (SFT) and DirectPreference Optimization (DPO).
• Develop and maintain training data pipelines, including data transformation, formatting,deduplication, filtering, and quality validation.
• Work extensivelywith the Hugging Face ecosystem, including Transformers, Datasets,and PEFT.
• Build and automate modelevaluation and benchmarking frameworks to assess model quality andperformance.
• Deploy and serve LLMmodels using AWS GPU/EC2 infrastructure and Amazon SageMaker.
• Optimize models forproduction through model quantization, inference optimization, andresource utilization.
• Build robust MLOpsand ML CI/CD pipelines covering model training, evaluation, packaging,deployment, and monitoring.
• Implement A/Btesting, Canary, and Shadow-mode deployments for safely introducingnew model versions into production.
• Develop mechanismsfor automated model promotion and rollback based on predefinedperformance and operational metrics.
• Implement productionmonitoring for model performance, latency, throughput, errors, GPUutilization, and resource consumption.
• Containerize MLworkloads using Docker and deploy/manage them using Kubernetes/AmazonEKS.
• Collaborate withData Scientists, ML Engineers, DevOps teams, and other stakeholders tobuild scalable and reliable AI/ML solutions.

Requirements

• Strong programmingexperience in Python .
• Hands-on experiencewith LLM fine-tuning , particularly SFT and DPO .
• Strong knowledge of HuggingFace Transformers, Datasets, and PEFT .
• Experience workingwith AWS GPU/EC2 and SageMaker for ML workloads.
• Strong understandingof MLOps, ML CI/CD, and model lifecycle management .
• Experience with LLMmodel serving and production deployment .
• Experience building trainingdata preparation and processing pipelines .
• Knowledge of modelevaluation, benchmarking, and performance optimization .
• Hands-on experiencewith model quantization .
  
• Experience implementing A/B, Canary, andShadow-mode deployments

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.

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.

Access to a dedicated break-out area with round-the-clock refreshments for relaxation and rejuvenation.