Research Platform Engineer: Multi-Tenant & Cloud

Career Techniques; New York (NY); Hybrid; USD 270,000 - 330,000; Full time

Job summary

Career Techniques seeks a senior platform engineer to build a multi-tenant research compute platform that orchestrates large-scale ML workloads across hybrid GPU/CPU infrastructures. You will create unified, elastic substrate enabling researchers to run simulations, distributed training, and complex pipelines with minimal overhead.

Responsibilities include architecting tenant isolation, multi-datacenter portability, and production-grade workflow orchestration, while delivering observability and

Qualifications

• Experience with HPC schedulers (e.g., Slurm) and containerized HPC execution.
• In-depth Kubernetes architecture and GPU-native schedulers.
• Experience with Ray, PyTorch, JAX in multi-node setups.

Responsibilities

• Elevate researcher experience by designing platform abstractions, APIs, and a durable job control plane.
• Architect multi-tenant scheduling and isolation across on-prem and cloud environments.
• Enable multi-datacenter portability and cloud bursting across on-premise datacenters and public cloud.
• Standardize workflow orchestration by evaluating and integrating production-grade engines.
• Build fault-tolerant pipelines with automated failure detection and retry mechanisms.
• Optimize data paths with high-speed networks and storage for large-scale workloads.

Skills

HPC schedulers

Kubernetes

Distributed ML

Workflow orchestration

Multi-platform infra

Storage & network

Observability

Leadership mindset

Tools

Ray

PyTorch

JAX

Job description

Career Techniques seeks a senior platform engineer to build a multi-tenant research compute platform that orchestrates large-scale ML workloads across hybrid GPU/CPU infrastructures. You will create unified, elastic substrate enabling researchers to run simulations, distributed training, and complex pipelines with minimal overhead.

Responsibilities include architecting tenant isolation, multi-datacenter portability, and production-grade workflow orchestration, while delivering observability and