MLOps Engineer

Connectio It; Dadri, Hyderabad, Bengaluru; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

Connectio It is seeking an experienced MLOps Engineer with a strong backend and ML operations background to design, deploy, and scale ML pipelines in production. The role focuses on building reliable cloud-native infrastructure, automating deployment workflows, and collaborating with data science and software teams.

You will work with Python, Docker, Kubernetes, and IaC tools to maintain secure and highly available systems, while ensuring monitoring, security, and automated recovery across

Qualifications

• 8+ years of experience in Backend Engineering and MLOps.
• Strong programming experience in Python.
• Hands-on experience with ML, including model development, training pipelines, and ML feature implementation.
• Experience with ML frameworks such as PyTorch, TensorFlow, and Scikit-learn.
• Strong expertise in developing REST APIs and backend applications.
• Hands-on experience with CI/CD tools such as Jenkins and GitHub CI/GitHub Actions.
• Experience with Docker and Kubernetes for containerization and orchestration.
• Strong knowledge of AWS cloud services and infrastructure.
• Experience implementing Infrastructure as Code (IaC) solutions.
• Hands-on experience with monitoring and logging tools such as Prometheus, Grafana, and the ELK Stack.
• Strong scripting skills in Python, Shell, and Groovy.
• Excellent analytical, troubleshooting, and problem-solving skills.
• Strong communication, collaboration, and organizational abilities.

Responsibilities

• Design, develop, and maintain scalable backend services using Python, APIs, and cloud infrastructure.
• Build, deploy, and optimize ML models, training pipelines, and ML-powered applications.
• Develop, maintain, and enhance CI/CD pipelines for applications across multiple platforms.
• Collaborate with development, data science, and engineering teams to streamline deployment processes and release strategies.
• Containerize and deploy applications using Docker and Kubernetes.
• Manage cloud infrastructure and ensure secure, scalable, and highly available environments.
• Implement Infrastructure as Code (IaC) for automated infrastructure provisioning and management.
• Monitor system performance, availability, and reliability using monitoring and logging tools.
• Ensure system security, stability, and automated recovery mechanisms.
• Conduct performance, security, and availability testing across environments.
• Troubleshoot production issues and optimize deployment workflows.
• Work independently while effectively collaborating with cross-functional engineering teams.
• Document deployment processes, infrastructure configurations, and operational procedures.

Skills

Python

ML Ops

REST APIs

CI/CD

AWS

Containers

Kubernetes

Terraform/IaC

Monitoring

Shell/Groovy

Tools

Docker

Kubernetes

AWS

Prometheus

Grafana

ELK Stack

Job description

Job Summary:

We are looking for an experienced MLOps Engineer with 8+ years of experience in backend engineering and machine learning operations. The ideal candidate will have strong expertise in Python, cloud infrastructure, CI/CD, containerization, and ML model deployment. You will be responsible for building and maintaining scalable ML pipelines, automating deployment workflows, managing cloud-native infrastructure, and collaborating with cross-functional teams to deliver reliable, secure, and high-performing machine learning solutions in production.

Key Responsibilities:

• Design, develop, and maintain scalable backend services using Python, APIs, and cloud infrastructure.
• Build, deploy, and optimize machine learning models, training pipelines, and ML-powered applications.
• Develop, maintain, and enhance CI/CD pipelines for applications across multiple platforms.
• Collaborate with development, data science, and engineering teams to streamline deployment processes and release strategies.
• Containerize and deploy applications using Docker and Kubernetes.
• Manage cloud infrastructure and ensure secure, scalable, and highly available environments.
• Implement Infrastructure as Code (IaC) for automated infrastructure provisioning and management.
• Monitor system performance, availability, and reliability using monitoring and logging tools.
• Ensure system security, stability, and automated recovery mechanisms.
• Conduct performance, security, and availability testing across environments.
• Troubleshoot production issues and optimize deployment workflows.
• Work independently while effectively collaborating with cross-functional engineering teams.
• Document deployment processes, infrastructure configurations, and operational procedures.

Required Skills:

• 8+ years of experience in Backend Engineering and MLOps.
• Strong programming experience in Python.
• Hands-on experience with Machine Learning, including model development, training pipelines, and ML feature implementation.
• Experience with ML frameworks such as PyTorch, TensorFlow, and Scikit-learn.
• Strong expertise in developing REST APIs and backend applications.
• Hands-on experience with CI/CD tools such as Jenkins and GitHub CI/GitHub Actions.
• Experience with Docker and Kubernetes for containerization and orchestration.
• Strong knowledge of AWS cloud services and infrastructure.
• Experience implementing Infrastructure as Code (IaC) solutions.
• Hands-on experience with monitoring and logging tools such as Prometheus, Grafana, and the ELK Stack.
• Strong scripting skills in Python, Shell, and Groovy.
• Excellent analytical, troubleshooting, and problem-solving skills.
• Strong communication, collaboration, and organizational abilities.