Tenstorrent
via Greenhouse
Staff Forward Deployed Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 2d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 40d ago
The date the source published, not the day we noticed it (2026-08-06). Last seen at its source 4h ago.
Is it remote?
The listing says yes
The location field doesn't say remote, so our assessment is based on the title or the description. Read the listing before applying.
Who may apply?
United States, Canada
The description states no restriction of its own. This is the source's own tag.
Pay
$100k–500k/yr
Read out of the job description by us, not from a structured field. Shown in the posting's own currency and period; we never convert.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
greenhouse employer's own board first seen 12d ago · last seen 4h ago
The listing
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities.
We’re looking for a Staff Forward Deployed Engineer who’s excited to build with the engineers using the AI computers Tenstorrent makes. You will create continuity between customers, engineering, and AI inference service products. This is an engineering role first: you contribute production code, operate deployments, and you can explain a trade-off to customer leadership as clearly as to core engineering teams. This is a high-autonomy role with direct customer impact.
This role is remote, based out of North America, with preference near one of our main hubs: Santa Clara, CA; Austin, TX; or Toronto, ON.
We welcome candidates at various experience levels for this role. 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.
Who You Are
- You understand how accelerator compute, memory, and networking topology constrain AI workloads, and don't treat hardware as a black box.
- You're an early adopter of AI for your work from coding to building agentic workflows that multiply your impact.
- You work directly with customers to understand their challenges and provide effective solutions.
- You are comfortable debugging across the full inference stack: from failing requests, through the serving layer, down to OOMs or kernel dispatch if need be.
- You bring feedback in the form of pull requests, reproducible code, benchmarks, and telemetry data.
What We Need
- Strong software engineering skills with 5+ years of relevant technical experience (e.g. Applied Engineer, Machine Learning Engineer, MLOps Engineer, Platform Engineer, Infrastructure Engineer, Site Reliability Engineer, Field Application Engineer).
- Experience turning ambiguous customer requirements or issues into verifiable acceptance criteria.
- Kubernetes and Helm experience at multi-node, HPC, or AI cluster scale.
- Experience with observability and infrastructure automation, e.g. Prometheus, Grafana, OpenTelemetry.
- Experience with LLM inference serving engines and technologies, e.g. vLLM, SGLang, Mooncake, NIM, Dynamo, LMCache.
What You Will Learn
- Where co-design of AI hardware and software translates into unique latency and throughput performance.
- How to scale disaggregated inference services on Kubernetes while balancing performance, reliability, and tactical tradeoffs.
- What makes enterprise AI deployments successful: from technical requirements through software delivery, cluster-scale validation, and production ownership.
- Why customer insights from the field shape the best products.
- How to build agentic workflows for asymmetric impact.
Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.
Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.
This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.