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Machine Learning Engineer, AI (FULLY REMOTE, USA)

Cisco

San Jose (CA)

Remote

USD 90,000 - 150,000

Full time

30+ days ago

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Job summary

An established industry player is seeking a Machine Learning Engineer to join their innovative Artificial Intelligence group. In this role, you will develop core AI/ML capabilities that power a comprehensive product portfolio, directly impacting customer success. Your responsibilities will include building AI platforms, collaborating with diverse teams, and ensuring the integration of cutting-edge advancements into the technology roadmap. This position offers a unique opportunity to work at the forefront of AI technology, contributing to the digital resiliency of clients while mentoring junior members and driving strategic initiatives. If you're passionate about AI and eager to make a difference, this is the perfect opportunity for you.

Qualifications

  • 3+ years of industry experience in AI/ML and related fields.
  • Experience with containerization and orchestration tools.

Responsibilities

  • Develop the AI/ML platform for cybersecurity and observability.
  • Collaborate with cross-functional teams to integrate AI solutions.

Skills

Problem-solving skills
Communication skills
Collaboration

Education

Bachelor's degree in Computer Science
Master's degree in Engineering

Tools

Docker
Kubernetes
Git
AWS
GCP
Azure
MLflow
Kubeflow

Job description

Machine Learning Engineer (MLE), Artificial Intelligence

Join us as we pursue our disruptive new vision to make machine data accessible, usable and valuable to everyone. We are a company filled with people who are passionate about our product and seek to deliver the best experience for our customers. At Splunk, we’re committed to our work, customers, having fun and most importantly to each other’s success. Learn more about Splunk careers and how you can become a part of our journey!

Role:

As a Machine Learning Engineer in the Artificial Intelligence group, you will be responsible for developing the core AI/ML capabilities to power the entire Splunk product portfolio and help our customers to drive their journey to digital resiliency. You will collaborate with cross-functional teams, mentor junior team members, and help drive the engineering roadmap of the area.

Responsibilities:

  1. Development of the AI/ML platform and infrastructure that drives our product’s key ML use cases in the cybersecurity and observability domains.
  2. Collaborate closely with software engineers, applied scientists, and product managers to integrate generative AI solutions into our products and services.
  3. Stay up to date with the latest developments in the field of AI/ML, and ensure that these advancements are properly incorporated into our technology roadmap.
  4. Actively participate in cross-functional discussions and strategic decisions related to AI directions and product roadmaps.

Requirements:

  1. Bachelor's or Master's degree in Computer Science, Engineering, or a related field with at least 3+ years of industry experience.
  2. Experience with containerization and orchestration tools (e.g., Docker, Kubernetes).
  3. Experience with model deployment and serving into production environments.
  4. Knowledge of version control systems, especially Git.
  5. Knowledge of CI/CD principles and tools.
  6. Familiarity with cloud platforms (AWS, GCP, Azure) and serverless architecture.
  7. Experience with MLOps platforms such as MLflow or Kubeflow.
  8. Previous experience working in cross-functional teams and collaborating with data scientists and DevOps teams.
  9. Problem-solving skills and the ability to troubleshoot complex issues.
  10. Communication skills with the ability to articulate complex technical concepts to both technical and non-technical audiences.

Splunk, a Cisco company, is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, national origin, genetic information, age, disability, veteran status, or any other legally protected basis.

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