Role : MLOps Engineer

Location : Bangalore

Experience : 8 Years

Job Summary :

We are seeking a highly skilled MLOps Engineer with 8 years of experience in backend engineering, cloud infrastructure, and Machine Learning Operations (MLOps). The ideal candidate will have a strong background in designing scalable ML platforms, automating model deployment pipelines, and managing cloud-native infrastructure. This role requires expertise in CI/CD, container orchestration, Infrastructure as Code (IaC), and modern machine learning frameworks to support the complete machine learning lifecycle.

Key Responsibilities :

- Design, build, and maintain scalable MLOps platforms to support model development, deployment, monitoring, and lifecycle management.
- Develop and maintain robust CI/CD pipelines for machine learning applications and backend services.
- Collaborate with data scientists, ML engineers, and software development teams to streamline model training, testing, deployment, and productionization.
- Build and automate machine learning training, validation, and deployment workflows.
- Develop backend services and APIs using Python to support ML-driven applications.
- Deploy and manage containerized applications using Docker and Kubernetes.
- Implement Infrastructure as Code (IaC) solutions to provision and manage cloud infrastructure.
- Monitor production systems and machine learning workloads using industry-standard monitoring and logging tools.
- Ensure system reliability, scalability, security, and high availability across cloud environments.
- Conduct performance tuning, system health checks, and security assessments to maintain production stability.
- Troubleshoot infrastructure, deployment, and application issues while driving continuous improvements in automation and operational efficiency.
- Collaborate with cross-functional teams to adopt DevOps and MLOps best practices.

Required Skills &

Experience :

- 8 years of experience in Backend Engineering, DevOps, Cloud Engineering, or MLOps.
- Strong backend development experience using Python, REST APIs,



and cloud-native application development.
- Hands-on experience with the complete Machine Learning lifecycle, including :
- Model development
- Model training
- Training pipelines
- Model deployment
- ML-powered application development
- Strong working knowledge of up-to-date Machine Learning frameworks such as :
- PyTorch
- TensorFlow
- Scikit-learn
- Experience designing and managing CI/CD pipelines using :
- Jenkins
- GitHub Actions
- GitLab CI or equivalent tools
- Hands-on experience with Docker and Kubernetes for containerization and orchestration.
- Strong expertise in cloud platforms such as :
- AWS
- ISCloud (or similar enterprise cloud platforms)
- Experience implementing Infrastructure as Code (IaC) using tools such as Terraform, CloudFormation, or equivalent.
- Experience with monitoring, logging, and observability tools including :
- Prometheus
- Grafana
- ELK Stack (Elasticsearch, Logstash, Kibana)
- Strong scripting skills using :
- Python

2.

Shell

Scripting

- Groovy
- Experience developing secure, scalable, and automated deployment processes.
- Knowledge of system security, performance optimization, high availability, and disaster recovery strategies.
- Strong troubleshooting and root cause analysis skills across cloud infrastructure and distributed systems.

Preferred Qualifications :

- Experience with enterprise-scale Machine Learning platforms and cloud-native architectures.
- Exposure to DevSecOps practices and automated security scanning.
- Familiarity with distributed data processing and workflow orchestration tools such as Airflow, Kubeflow, or MLflow is an advantage.
- Experience working in Agile/Scrum environments.
- Relevant certifications in AWS, Kubernetes, Docker, DevOps, or Machine Learning are preferred.

Preferred Competencies :

- Strong analytical and problem-solving abilities.
- Ability to work independently while collaborating effectively with cross-functional engineering teams.
- Excellent communication, stakeholder management, and organizational skills.
- Strong focus on automation, operational excellence, and continuous improvement.

Work Location :

Bangalore

📌 MLOps Engineer - CI/CD Pipeline (India)
🏢 SYSMIND
📍 India