Tenstorrent currently has 27 active AI-related job listings, with a significant majority, 81%, focused on serving infrastructure. Engineering roles comprise all of their AI hiring. The company is primarily hiring in the United States and Canada. Frequent technical tags include model_serving, inference_infra, and agent_orchestration, suggesting a focus on AI model deployment and management. In the last 30 days, Tenstorrent has not posted any new AI roles, representing a 100% decrease compared to the previous 30-day period.
Currently tracking 22 active AI roles, down 50% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $100k–$500k (avg $300k).
Tenstorrent currently has 25 active AI-related roles in our index. The most common open titles are: Sr. Engineer, Software - AI Compiler (2), AI/ML Physical Design Flow Engineer, C++ Machine Learning Engineer, Models Training, Design Verification Lead, AI Hardware , Infrastructure and Platform Development Engineer. Most positions are in Engineering and Research.
Tenstorrent's active AI hiring is concentrated in: serving infrastructure (80%), agents (8%), application (4%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Tenstorrent is hiring AI talent in: United States (10 roles), Canada (8 roles), Serbia (4 roles), Poland (2 roles).
Job postings at Tenstorrent most frequently reference: inference infra, model serving, fine tuning, agent orchestration, vision.
In the past 30 days, Tenstorrent has posted 1 new AI-related role.
| Title | Stage | AI score |
|---|---|---|
| Sr. Engineer, Software - AI Compiler Sr. Engineer, Software - AI Compiler role at Tenstorrent focused on developing TT-Forge, an MLIR-based compiler for Tenstorrent hardware, optimizing AI models for training and inference. | Serve | 8 |
| Sr. Engineer, Kernel Development and Optimization Sr. Engineer, Kernel Development and Optimization at Tenstorrent, focusing on designing, implementing, and optimizing performance-critical kernels for AI hardware, including matrix multiplication and attention primitives. The role involves host-side orchestration, parallelization, developing benchmarks and tests, and collaborating with compiler, runtime, ML, and hardware teams to integrate kernels into production systems. Experience with C++, low-level software, concurrency, and data-driven optimization is required. | Serve |
| 7 |
| Sr Engineer, Server Inference The role focuses on developing software for state-of-the-art AI inferencing on Tenstorrent's hardware, including designing APIs, deploying workloads, and benchmarking inference speed. It involves optimizing end-to-end ML inference on custom silicon and building scalable software interfaces. | Serve | 7 |
| Staff Infrastructure Engineer - Models Infrastructure Engineer focused on building and operating Kubernetes-native applications and services for large-scale AI workloads, including inference and training. The role involves developing operators, APIs, and automation to improve deployment, scaling, monitoring, and reliability of AI infrastructure. | Serve | 5 |
| Staff Technical Program Manager Technical Program Manager to lead programs that advance and accelerate AI software performance on custom high-performance hardware. Drive cross-functional initiatives spanning AI model integration and performance optimization across the software stack. Partner with engineering leads, product teams, and leadership to deliver reliable, scalable solutions. | — | 5 |
| Experienced Technical Recruiter Experienced Technical Recruiter for an AI company, focusing on hiring deeply technical roles in AI, ML, systems, hardware, or infrastructure. The role involves full-cycle ownership, proactive sourcing, and acting as a trusted advisor to hiring managers. | — | 5 |
| Sr. Staff Engineer, Driver Tenstorrent is seeking a Sr. Staff Engineer, Driver to focus on the user-mode driver and interface layer for their AI hardware. This role involves designing and evolving high-performance APIs, defining driver interfaces, collaborating with kernel and hardware teams, driving performance engineering, and supporting external integrations, including in safety-critical use cases. | — | 0 |