MLOps / AI Engineer

VMC Soft Technologies, Inc; Hyderabad; On-site; INR 2,000,000 - 4,200,000; Full time

Job summary

VMC Soft Technologies, Inc is seeking an experienced MLOps / AI Engineer to build, deploy, and manage enterprise AI/ML platforms and production-grade ML/LLM applications. The ideal candidate should have expertise in Python, Azure ML, Docker, Kubernetes, CI/CD, MLOps, LLMs, RAG, and cloud platforms (Azure/AWS/GCP).

Looking to join a team that delivers scalable AI solutions with modern tooling and robust governance, you will own end-to-end pipelines and drive best practices across the ML lifecycle.

Qualifications

• 8–10 years of MLOps / AI engineering experience.
• Proficiency in Python and Linux.
• Experience with Azure ML, AWS, and GCP.
• Docker and Kubernetes expertise.
• CI/CD with GitHub Actions, Azure DevOps or Jenkins.
• Infrastructure as code with Terraform/ARM/Bicep/CloudFormation.
• MLflow, Kubeflow, SageMaker, or Azure ML experience.
• LLMs, RAG, embeddings, vector databases considered a plus.

Responsibilities

• Build end-to-end MLOps pipelines for model training, deployment, monitoring, retraining, and lifecycle management.
• Develop ML models using Python and Azure ML.
• Deploy AI workloads using Docker and Kubernetes.
• Build CI/CD pipelines and automate infrastructure with IaC tools.
• Develop Generative AI solutions using LLMs, RAG, embeddings and vector databases.
• Integrate with Azure OpenAI, OpenAI, Anthropic, or AWS Bedrock.
• Monitor model performance, drift, logging, tracing, and production health.
• Ensure security, IAM, secrets management, encryption, and governance.
• Provide production support and incident resolution.

Skills

MLOps / AI Engineer experience

Python

Linux

Azure ML

AWS

GCP

CI/CD

Observability

Education

Bachelor's or Master's in CS/AI/Data Science

Tools

Docker

Kubernetes

Terraform

ARM

Bicep

CloudFormation

MLflow

Kubeflow

SageMaker

Azure DevOps

GitHub Actions

Prometheus

Grafana

CloudWatch

Azure Monitor

Job description

Job Summary

Looking for an experienced

Python, Azure ML, Docker, Kubernetes, CI/CD, MLOps, LLMs, RAG, and cloud platforms (Azure/AWS/GCP).

Key Responsibilities

• Build and maintain end-to-end MLOps pipelines for model training, deployment, monitoring, retraining, and lifecycle management.
• Develop ML models using Python and Azure Machine Learning.
• Deploy AI workloads using Docker and Kubernetes.
• Build CI/CD pipelines and automate infrastructure using Terraform/Bicep/ARM/CloudFormation.
• Develop LLM & Generative AI solutions using RAG, Prompt Engineering, Embeddings, Vector Databases, and Agentic AI.
• Integrate with Azure OpenAI, OpenAI, Anthropic Claude, or AWS Bedrock.
• Monitor model performance, drift, logging, tracing, and production health.
• Implement security, IAM, secrets management, encryption, and governance.
• Provide production support and incident resolution.

Job Title

MLOps / AI Engineer

Experience: 8 10 Years

Job Summary

Looking for an experienced MLOps / AI Engineer to build, deploy, and manage enterprise AI/ML platforms and production-grade ML/LLM applications. The ideal candidate should have expertise in Python, Azure ML, Docker, Kubernetes, CI/CD, MLOps, LLMs, RAG, and cloud platforms (Azure/AWS/GCP).

Key Responsibilities

• Build and maintain end-to-end MLOps pipelines for model training, deployment, monitoring, retraining, and lifecycle management.
• Develop ML models using Python and Azure Machine Learning.
• Deploy AI workloads using Docker and Kubernetes.
• Build CI/CD pipelines and automate infrastructure using Terraform/Bicep/ARM/CloudFormation.
• Develop LLM & Generative AI solutions using RAG, Prompt Engineering, Embeddings, Vector Databases, and Agentic AI.
• Integrate with Azure OpenAI, OpenAI, Anthropic Claude, or AWS Bedrock.
• Monitor model performance, drift, logging, tracing, and production health.
• Implement security, IAM, secrets management, encryption, and governance.
• Provide production support and incident resolution.

Mandatory Skills

• 8 10 years of MLOps / AI Engineering experience.
• Python & Linux.
• Azure ML / AWS / GCP.
• Docker & Kubernetes.
• CI/CD (GitHub Actions, Azure DevOps, Jenkins).
• Terraform / ARM / Bicep / CloudFormation.
• MLflow / Kubeflow / SageMaker / Azure ML.
• LLMs, RAG, Prompt Engineering, Embeddings, Vector Databases.
• Azure OpenAI / OpenAI / Anthropic / AWS Bedrock.
• Monitoring, Model Drift, Observability.

Good-to-Have Skills

• Agentic AI Frameworks.
• MLflow / Kubeflow.
• Prometheus, Grafana, CloudWatch, Azure Monitor.
• ITIL / Production Support.
• High Availability AI Platforms.

Education

• Bachelor's or Master's degree in Computer Science, AI, Data Science, Information Technology, or related field.