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 :

1. Model development

2. Model training

3. Training pipelines

4. Model deployment

5. ML-powered application development

- Strong working knowledge of modern Machine Learning frameworks such as :

1. PyTorch

2. TensorFlow

3. Scikit-learn

- Experience designing and managing CI/CD pipelines using :

1. Jenkins

2. GitHub Actions

3. GitLab CI or equivalent tools

- Hands-on experience with Docker and Kubernetes for containerization and orchestration.

- Strong expertise in cloud platforms such as :

1. AWS

2. 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 :

1. Prometheus

2. Grafana

3. ELK Stack (Elasticsearch, Logstash, Kibana)

- Strong scripting skills using :

1. Python

2. Shell Scripting

3. 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