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.
- Robust 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.

📌 MLOps Engineer (Noida)
🏢 Connectio It
📍 Noida