ML Ops Engineer

Futops Technologies India Private Limited; India; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Futops Technologies India Private Limited seeks an experienced MLOps/DevOps Engineer to support a large-scale migration and modernization program. You will build containerized, cloud-native platforms using OpenShift and AWS ROSA, and operate CI/CD pipelines for ML workloads.

You will collaborate with platform, ML, and application teams to migrate, deploy, and manage workloads in a modern DevOps/MLOps environment, applying IaC and Observability best practices.

Qualifications

• 5+ years of hands-on DevOps/MLOps in production environments.
• Strong experience with Docker, Kubernetes, and container orchestration.
• OpenShift experience; AWS ROSA exposure is a strong advantage.
• Solid understanding of AWS cloud services, networking, IAM, and security best practices.
• Experience with IaC using Terraform/Terragrunt.
• Scripting skills in Python, Bash, Go, or Ruby.
• Good knowledge of Linux systems, containers, and distributed systems.
• Experience with Prometheus, Grafana, and ELK for monitoring/observability.
• Familiarity with CI/CD tools and GitOps workflows.

Responsibilities

• Lead and execute application and ML workload migrations to containerized platforms.
• Design, deploy, and manage infrastructure on AWS with ROSA focus.
• Build and operate CI/CD pipelines for application and ML lifecycle management.
• Containerize apps using Docker and deploy on Kubernetes/OpenShift.
• Implement MLOps for model training, deployment, versioning, and monitoring.
• Collaborate with development and data science teams to optimize performance and cost.
• Ensure platform reliability via monitoring, alerting, logging, and automation.
• Participate in troubleshooting and continual improvement initiatives.

Skills

Docker

Kubernetes

OpenShift

AWS ROSA

Terraform

Terragrunt

Python

Bash

Linux

CI/CD

GitOps

Education

B.Tech / B.E. (CS/IT) or equivalent

Tools

Prometheus

Grafana

ELK

OpenShift

Job description

Experience: 5+ years

Education: B.Tech / B.E. (Computer Science, IT, or related discipline) or equivalent practical experience

Role Overview

We are looking for experienced MLOps / DevOps Engineers to support a large-scale application migration and modernization program. The role involves migrating existing applications and ML workloads to containerized, cloud-native platforms using OpenShift and AWS ROSA, while ensuring scalability, reliability, and operational excellence.

You will work closely with platform, ML, and application teams to redesign, migrate, deploy, and operate workloads in a modern DevOps/MLOps ecosystem.

Key Responsibilities

• Lead and execute application and ML workload migrations from legacy or VM-based environments to containerized platforms.
• Design, deploy, and manage infrastructure on AWS, with a strong focus on ROSA (Red Hat OpenShift on AWS).
• Build and operate CI/CD pipelines for application and ML lifecycle management.
• Containerize applications using Docker and deploy/manage them on Kubernetes/OpenShift.
• Implement MLOps practices for model training, deployment, versioning, monitoring, and rollback.
• Collaborate with development and data science teams to optimize performance, cost, and scalability.
• Ensure platform reliability through monitoring, alerting, logging, and automation.
• Participate in troubleshooting, root cause analysis, and continuous improvement initiatives.

Required Skills & Experience

• 5+ years of hands-on DevOps / MLOps experience in production environments.
• Strong experience with Docker, Kubernetes, and container orchestration.
• Practical experience with OpenShift; AWS ROSA exposure is a strong advantage.
• Solid understanding of AWS cloud services, networking, IAM, and security best practices.
• Experience with Infrastructure as Code (IaC) using Terraform / Terragrunt.
• Strong scripting skills in Python, Bash, Go, or Ruby.
• Good working knowledge of Linux systems, container runtimes, and distributed systems.
• Experience with monitoring and observability tools such as Prometheus, Grafana, and ELK.
• Familiarity with CI/CD tools and GitOps-based workflows.

Good to Have

• Exposure to ML frameworks, GPU-based workloads, and large-scale ML operations.
• Experience operating or scaling systems like Elasticsearch, Kafka, Spark, or HBase.
• Understanding of model lifecycle management, feature stores, and ML pipelines.
• Experience in cloud migration or modernization programs.
• Knowledge of security, compliance, and platform hardening in Kubernetes/OpenShift environments.

Soft Skills

• Strong analytical and problem-solving abilities.
• Clear communication and documentation skills.
• Ability to work in cross-functional teams and fast-paced environments.