Talenthop
United States
New
ML Platform Engineer
Machine Learning Full-time Mid-Senior level 57m ago
- AI
- Artificial Intelligence
- C++
- Cloud
AI Summary
Designs and oversees large-scale AI/ML infrastructure for a healthcare leader, focusing on multi-tenant compute, distributed training, and secure model-serving across hybrid cloud environments. Collaborates with infrastructure, security, and engineering teams to enhance reliability, scalability, cost efficiency, and deployment speed. Requires 10+ years of experience in infrastructure, DevOps, SRE, or ML platform engineering with deep expertise in Kubernetes, GPU technologies, and hybrid AI platforms.
Key Highlights
10+ years of experience in infrastructure, DevOps, SRE, or ML platform engineering required
Expertise in Kubernetes/OpenShift, NVIDIA GPU technologies, and hybrid AI platforms mandatory
Remote role with U.S.-wide flexibility
Key Responsibilities
Design and manage multi-tenant AI/ML compute platforms
Set standards for distributed training and model-serving infrastructure
Collaborate with stakeholders to improve platform reliability, scalability, and cost efficiency
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Technical Skills Required
Benefits & Perks
Comprehensive benefits package
Incentive and recognition programs
Equity stock purchase option
401k contribution
Remote work flexibility (U.S.-wide)
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Nice to Have
Experience with GitOps tooling for multi-cluster management
HPC/AI networking expertise
Architecting hybrid AI platforms with major cloud providers
Job Description
For our client, we are seeking a Principal AI/ML Platform Engineer to join the team of a leader in the Healthcare space.
This role will shape the architecture and operating model for large-scale AI and ML infrastructure that supports healthcare innovation. You will define standards for multi-tenant compute platforms, distributed training performance, and secure model-serving capabilities across hybrid cloud environments. The position partners closely with infrastructure, security, and engineering stakeholders to improve reliability, scalability, cost efficiency, and deployment velocity.
Location:
Remote
Compensation:
$164,600 – $282,200 annually
Responsibilities
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