Staff Platform Engineer, Tenstorrent

Infrastructure

$100-500k

Salary range includes base and variable compensation targets. Salary is benchmarked based on US rates and may vary depending on the location

Kubernetes

Python

Rust

Senior and Expert level

Austin

San Francisco Bay Area

Toronto

Building computers for AI

Be an early applicant

Building computers for AI

501-1000 employees

B2BArtificial IntelligenceEnterpriseManufacturingDeep TechMachine Learning

Be an early applicant

$100-500k

Salary range includes base and variable compensation targets. Salary is benchmarked based on US rates and may vary depending on the location

Kubernetes

Python

Rust

Senior and Expert level

Austin

San Francisco Bay Area

Toronto

501-1000 employees

B2BArtificial IntelligenceEnterpriseManufacturingDeep TechMachine Learning

Company mission

To bring unique solutions to the problems facing AI and machine learning.

Job

Company

Role

Who you are

We welcome candidates at various experience levels. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting
Proven experience designing and delivering distributed systems on Kubernetes at scale
Strong skills in Python, Go, or Rust for building platform services and automation tooling
An understanding of microservice communication patterns, tracing, and performance debugging in production environments
A background in architecting CI/CD and deployment strategies for large, multi-team engineering organizations

What the job involves

Tenstorrent’s infrastructure team designs and builds the software platforms that power AI development, training, and deployment across our full stack
This role focuses on designing scalable services, architecting distributed systems, and building Kubernetes-based platforms that support a range of workloads from compiler toolchains to ML training pipelines
You’ll define how our software is deployed, scaled, and evolved to meet the needs of next-generation AI hardware
Architect and implement distributed systems that run on Kubernetes, supporting software, compiler, and ML workloads
Design internal services, APIs, and automation frameworks that improve developer productivity and accelerate release cycles
Build platform capabilities for deploying, scaling, and monitoring microservices in hybrid and multi-cluster environments
Establish patterns for resilience, fault tolerance, and scalability across the software stack
What You’ll Learn:
How to integrate compiler stacks, ML frameworks, and runtime services into a unified Kubernetes-based platform
New techniques for scaling AI workloads across clusters and geographies
How to design software platforms that balance performance, reliability, and developer efficiency
Our approach to delivering open, high-performance AI infrastructure that supports rapid iteration

Our take

Advances in artificial intelligence apps, combined with a global chip shortage, are strong tailwinds for chip processor Tenstorrent. The semi-conducter developer is designing specialized chips for running artificial intelligence applications, building chips for what it calls "software 2.0".

The company’s unique approach is to build for this future software, which it believes will be written at a higher level. Combining this with conditional computing, Tenstorrent supports a scalable distributed network approach that is analogous to a human brain.

While the market for specialised AI hardware is destined to be gigantic, the company has to compete with a plethora of hopeful startups (as well as major tech companies like NVIDIA and Qualcomm). That said, Tenstorrent boasts an excellent trajectory so far, with its latest moves including unveiling its high-end Wormhole AI processors, and a partnership with LG which will see the development of chips for "Affectionate Intelligence".

Kirsty

Company Specialist at Welcome to the Jungle

Insights

Top investors

52% employee growth in 12 months

Glassdoor (4.5)

Company

Funding (last 2 of 7 rounds)

Dec 2024

$700m

SERIES D

Jun 2024

$300m

LATE VC

Total funding: $1.3bn

Company HQ

Flemingdon Park, Toronto, ON

Leadership

Jim Keller

(CEO)

Previously Senior VP of Silicon Engineering at Intel Corporation, VP of Autopilot Hardware Engineering at Tesla, Corporate VP and Chief Architect at AMD, and VP of Engineering at Apple.

Milos Trajkovic

(Co-Founder & Director of Hardware Engineering)

Former Manager of Firmware Design Engineering at AMD, and FPGA design engineer at Signum Concepts.

Ivan Hamer

(Co-Founder)

Former Consulting Software/Embedded Engineer at AMD, and Senior Software Developer at iNTERFACEWARE.

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