Software Engineer, ML
Description
Overview
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, microservices, and cloud-based architectures.
- Familiarity with Kubernetes, Docker, and containerized 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).
Thank you for your interest in Splunk!