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Software Engineer, ML

Software Engineer, ML

Splunk

4 - 8 years

0 Lacs

karnataka

Posted:6 days ago| Platform: Shine logo

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Skills Required

python kubernetes devops aws gcp azure microservices docker terraform cloudformation restful api development cicd

Work Mode

On-site

Job Type

Full Time

Job Description

As a Software Engineer in the Artificial Intelligence group, you will contribute to developing and optimizing the backend infrastructure that supports AI-driven solutions. You will work closely with machine learning engineers and cross-functional teams to build scalable backend services, automate deployments, and improve system performance. Your role will focus on Python-based backend development, Kubernetes operations, and DevOps best practices to ensure reliable and efficient AI model deployments. Responsibilities - Develop and maintain backend services and APIs that support AI models and intelligent assistants. - Improve scalability and performance of AI model serving and API interactions. - Ensure system reliability by implementing logging, monitoring, and alerting solutions. - Assist in deploying AI models using Kubernetes and Docker, ensuring smooth model integration into production. - Contribute to CI/CD pipelines for AI applications, automating model testing and deployments. - Work on data pipelines and optimize storage and retrieval for AI workloads. - Work on infrastructure automation using Terraform, CloudFormation, or other Infrastructure as Code (IaC) tools. - Support cloud-based deployments on AWS, GCP, or Azure, optimizing resource usage. - Work closely with AI/ML engineers to understand infrastructure requirements for AI solutions. - Participate in code reviews, architecture discussions, and knowledge-sharing sessions. - Continuously learn and improve skills in backend development, cloud technologies, and DevOps. Requirements - 4 years of experience in backend development using Python (preferred) or Java. - Experience with RESTful API development, micro-services, and cloud-based architectures. - Familiarity with Kubernetes, Docker, and containerised deployments. - Hands-on experience with CI/CD tools (e.g., Jenkins, GitHub Actions, ArgoCD). - Basic understanding of cloud platforms (AWS, GCP, or Azure) and their services. - Strong problem-solving skills and a willingness to learn new technologies. Preferred Experience - Exposure to AI/ML pipelines, model serving, or data engineering workflows. - Experience with monitoring and observability tools (e.g., Prometheus, Grafana, OpenTelemetry).,

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Software Engineer, ML