Machine Learning Engineer (MLE), Artificial Intelligence
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Job Description
About the Company:
Splunk is a company passionate about making machine data accessible, usable, and valuable to everyone. They are committed to their work, customers, fostering a fun work environment, and prioritizing the success of their employees. They are actively pursuing a disruptive vision in their field.
Job Description: Machine Learning Engineer (MLE), Artificial Intelligence
This role involves developing core AI/ML capabilities to power Splunk’s product portfolio, helping customers achieve digital resiliency. The position requires collaboration with various teams (software engineers, applied scientists, product managers) and mentoring junior team members. This Machine Learning Engineer will also contribute to the engineering roadmap.
Responsibilities:
• Development of AI/ML platform and infrastructure: Building the core AI/ML systems that underpin key machine learning use cases within the cybersecurity and observability domains of Splunk’s products.
• Generative AI integration: Collaborating to integrate generative AI solutions into Splunk’s products and services.
• Staying current with AI/ML advancements: Keeping abreast of the latest developments in AI/ML and incorporating these advancements into Splunk’s technology roadmap.
• Strategic participation: Actively participating in cross-functional discussions and strategic decisions related to AI directions and product roadmaps.
Requirements:
• Education and Experience: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field with 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).
• Collaboration and Communication: Experience working in cross-functional teams, collaborating with data scientists and DevOps teams. Excellent problem-solving and communication skills (articulating complex technical concepts to both technical and non-technical audiences).
Compensation and Benefits:
The job posting includes a detailed breakdown of base pay ranges varying by location (SF Bay Area, Seattle, NYC, etc.) and mentions additional compensation elements like incentives, equity, and long-term cash awards. A competitive benefits package including medical, dental, vision, 401(k), paid time off, and more is also highlighted. The company offers flexibility with working arrangements (remote and/or in-office).
