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Photon

Cortex Principal / Lead ML Engineer - Enterprise Machine Learning Platform (Multi-Cloud) | Onsite

Posted Yesterday
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In-Office or Remote
Hiring Remotely in United States
64K-226K Annually
Expert/Leader
In-Office or Remote
Hiring Remotely in United States
64K-226K Annually
Expert/Leader
Design and implement enterprise-scale, multi-cloud ML platform architecture. Lead end-to-end MDLC, enforce data/compute separation, data protection, security and governance. Build on Kubernetes (OpenShift, GKE), deliver hands-on platform solutions and agentic AI prototypes, and present to executives.
The summary above was generated by AI

We are looking for a seasoned architect with hands-on experience designing and implementing enterprise-scale AI platforms. Key qualifications include: 

  • Expertise in end-to-end enterprise ML platform architecture, including multi-cloud environments 
  • Strong knowledge of data and compute separation and integration patterns 
  • Comprehensive understanding of the Model Development Lifecycle (MDLC) 
  • Experience with data protection strategies (data at rest and in transit) 
  • Deep understanding of security, technology, and data governance controls 
  • Strong expertise in Kubernetes, including OpenShift (OCP) and GKE 
  • Proven hands-on experience building enterprise ML platforms 
  • Experience with agentic AI solutions and modern development approaches (e.g., rapid prototyping / “vibe coding”) 
  • Excellent communication and executive presentation skills

Compensation, Benefits and Duration

Minimum Compensation: USD 64,000
Maximum Compensation: USD 226,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full-time employees.
This position is available for independent contractors
No applications will be considered if received more than 120 days after the date of this post
 

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