AI / MLOps Engineer

Quick Facts

• Role: AI / MLOps Engineer

Description

Design, deploy, and operate production-grade AI platforms and machine learning solutions. You will build scalable ML pipelines for training, deployment, and monitoring, automate data ingestion and feature engineering, and integrate AI/ML models into enterprise applications and APIs. You’ll also develop CI/CD pipelines for ML systems, monitor performance and drift, and deploy workloads using Docker and Kubernetes while ensuring security, compliance, and operational excellence.

Responsibilities

• Design and implement scalable ML pipelines for training, deployment, and monitoring

• Automate data ingestion, preprocessing, and feature engineering workflows

• Integrate AI/ML models into enterprise applications and APIs

• Develop and maintain CI/CD pipelines for Machine Learning systems

• Monitor model performance, detect model drift, and automate retraining

• Deploy AI workloads using Docker and Kubernetes

• Ensure security, compliance, and operational excellence across AI services

• Collaborate with Data Scientists, DevOps Engineers, Software Developers, and business stakeholders

Requirements

• 3+ years of experience in AI/ML Engineering, MLOps, Machine Learning Engineering, or related roles

• Strong Python programming skills

• Experience deploying ML models into production environments

• Hands-on experience with Azure, AWS, or GCP

• Solid knowledge of Docker, Kubernetes, and CI/CD practices

• Experience with monitoring and observability tools

• Understanding of software engineering best practices and infrastructure automation

• Experience working in Agile environments

Benefits

• Work on production-grade AI operations, automation, and modern MLOps practices