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Engineering

Software Engineer, ML

  • - No Remote

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).

 

Note:

Splunk's Hiring Practices

Splunk turns machine data into answers. Organizations use market-leading Splunk solutions with machine learning to solve their toughest IT, Internet of Things and security challenges.

We value diversity, equity, and inclusion at Splunk and are committed to equal employment opportunity. Qualified applicants receive consideration for employment without regard to race, religion, color, national origin, ancestry, sex, gender, gender identity, gender expression, sexual orientation, marital status, age, physical or mental disability or medical condition, genetic information, veteran status, or any other consideration made unlawful by federal, state or local laws. We consider qualified applicants with criminal histories, consistent with legal requirements. Click here to review the US Department of Labor’s EEO is The Law notice. Please click here to review Splunk’s Affirmative Action Policy Statement. If you need assistance or an accommodation to apply or during the hiring process, please let us know by completing our Accommodation Request form.

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