Devops Specialist

Experience: 8-10 years of experience as an IT Infrastructure and Operations ManagerRequired Qualification: Bachelor’s degree or equivalent qualification in Information Technology, Computer Science, or relevant subjectLocation: Gurgaon/BangaloreWHAT YOU’LL DO:● Provide inputs for IT operations in DevOps, SecOps, FinOps, and MLOps and support strategy planning.● Develop service-level agreement key performance indicators (KPIs) and dashboards for all operations, including ML models.● Monitor service-level dashboards to ensure compliance with KPIs and SLAs, particularly those related to model performance (e.G., inference time, latency, accuracy, and error rates).● Automate detection of SLA non-compliance and implement corrective actions to address issues.● Automate tasks such as application and model deployment, configuration, and updates, utilizing CI/CD pipelines.● Build and maintain monitoring and alerting platforms for various applications and ML models, ensuring high availability and real-time performance tracking.● Apply DevOps methodologies for CI/CD, security, and monitoring across traditional and ML workloads.● Engage in upcoming projects' infrastructure to ensure they are scalable, fault-tolerant, and optimized for both general applications and machine learning pipelines.● Regularly review and optimize costs for multiple applications and ML workloads running on the cloud.● Maintain high availability during traffic spikes, disasters, and malicious attacks, including ML model serving.● Work closely with software developers and data scientists to ensure our systems, applications, and ML models are monitored and available 24x7.WHAT WE LOOK FOR:● Proven experience in deploying and maintaining multi-tiered infrastructure and applications, including ML pipelines.● Basic knowledge of Relational Databases and NoSQL databases.● Experience with real-time failover architecture, principles, and processes.● Excellent communication and technical writing skills;

ability to convey complex technical designs through diagrams, documents, and presentations.● Ability to work with cross-functional teams to develop automation solutions for services, including ML models.● Be an advocate for a DevOps mindset and culture, promoting collaboration, flexibility, cross-domain knowledge, and knowledge sharing. A self-driven individual who understands requirements and develops and coaches others as needed.● Background in infrastructure and configuration as code platforms (Terraform, Ansible, etc.).● Hands-on experience managing and scaling CI/CD platforms (Jenkins, GitHub, etc.).● Availability to participate in on-call rotations to respond to and handle after-hour issues.● Hands-on experience with AWS services (EC2, RDS, S3, IAM, etc.).● Knowledge of network protocols, monitoring systems (like New Relic, Datadog, Grafana, etc.), and database administration (MySQL, Aerospike, MongoDB, etc.).● Hands-on experience with production-grade container orchestrators (Kubernetes, Nomad).● Knowledge of Hadoop, AWS Kinesis, HA Proxy, and Aerospike is a plus.● Experience working with log analysis and monitoring tools in a distributed application scenario.● Experience in troubleshooting system issues causing downtime or performance degradation.● Experience working in an Agile environment.● Extensive knowledge of load balancing and auto-scaling in cloud environments.ADDITIONAL RESPONSIBILITIES IN MLOps:● Develop and define KPIs specific to MLOps, such as inference times, model accuracy, latency, training times, and error rates, to ensure the effectiveness and reliability of ML models in production.● Implement real-time monitoring and alerting for ML models to detect deviations in performance and automatically trigger workflows to mitigate SLA breaches.● Coordinate asynchronously with a globally distributed team working across different time zones to provide 24/7 support for all MLOps activities.● Optimize cloud resources for ML workloads by utilizing cost-effective solutions such as spot instances for training and analysis, and regularly review and optimize costs associated with GPU/TPU usage.● Enhance observability and traceability across ML pipelines, ensuring robust audit trails and quick identification of data or model-related issues.● Develop and implement advanced security measures to protect sensitive data used in ML models and ensure compliance with data security and privacy regulations.BONUS:● Experience designing high-availability & cloud-native solutions.● Python & Bash coding skills.● Knowledge of Excel.● Experience in low-latency architectures (Ad Tech RTB, Trading, etc.).● Genuine interest in Open Source and/or personal projects.● Solid understanding of security mechanisms for operating systems and cloud services.

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