Machine Learning Engineer (MLE), Artificial Intelligence
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Job Description
About the Company:
Splunk, a Cisco company, is focused on making machine data accessible, usable, and valuable to everyone. They are a product-driven company with a passionate team committed to customer experience and internal success. They offer flexible work arrangements, including remote and in-office options.
Job Description: Machine Learning Engineer (MLE), Artificial Intelligence
This role sits within Splunk’s Artificial Intelligence group. The primary responsibility is developing core AI/ML capabilities to power Splunk’s product portfolio, particularly focusing on cybersecurity and observability. The position requires a significant contribution to the company’s journey towards digital resiliency.
Detailed Responsibilities:
• Developing the AI/ML platform and infrastructure supporting key machine learning use cases within the cybersecurity and observability domains.
• Close collaboration with software engineers, applied scientists, and product managers to integrate generative AI solutions into Splunk’s products and services.
• Staying current with AI/ML advancements and incorporating those advancements into Splunk’s technology roadmap.
• Active participation in cross-functional discussions and strategic decisions related to AI directions and product roadmaps.
• Mentoring junior team members.
• Driving the engineering roadmap for the AI/ML area.
Detailed Requirements:
• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Experience: At least 3+ years of industry experience.
• Technical Skills:
• Experience with containerization and orchestration tools (Docker, Kubernetes).
• Experience with model deployment and serving in production environments.
• Proficiency in version control systems (Git).
• Understanding of CI/CD principles and tools.
• Familiarity with cloud platforms (AWS, GCP, Azure) and serverless architecture.
• Experience with MLOps platforms (MLflow or Kubeflow).
• Soft Skills:
• Proven ability to work effectively in cross-functional teams (data scientists, DevOps).
• Excellent problem-solving and troubleshooting skills.
• Strong communication skills, able to articulate complex technical concepts to both technical and non-technical audiences.
Compensation: The base pay range varies significantly depending on location. Specific ranges are provided for the San Francisco Bay Area, Seattle Metro, New York City Metro Area, other US locations (excluding those previously mentioned), and international locations. In addition to base pay, the role includes incentive compensation and potential equity or long-term cash awards. A comprehensive benefits package is also offered, including medical, dental, vision, 401(k), paid time off, and more.
