Machine Learning Engineer, Tenstorrent

ML Models

$100-500k

OTE

Python

PyTorch

Junior, Mid and Senior level

San Francisco Bay Area

More information about location

Next-generation computing company building computers for AI

Open for applications

Next-generation computing company building computers for AI

1001+ employees

B2BArtificial IntelligenceEnterpriseManufacturingDeep TechMachine Learning

Open for applications

$100-500k

OTE

Python

PyTorch

Junior, Mid and Senior level

San Francisco Bay Area

More information about location

1001+ 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

If you love the craft of ML and want to work on models that are used in real world applications, you’ll feel right at home
Confident with Python programming and hands-on experience with PyTorch for developing deep learning models
Driven by curiosity and a desire to experiment, always seeking to understand how complex systems work and how to make them better
Possess a deep understanding of ML model architectures, enabling optimization of both individual components and their interactions
Easy to work with and excited to collaborate across software and hardware teams
Hands-on experience bringing up state-of-the-art ML models on new hardware platforms
Strong debugging instincts to investigate performance issues, tune architectures, and boost model accuracy and robustness
Working knowledge of model optimization techniques—like quantization, sparsity, and attention—as well as hardware features such as matrix engines and memory hierarchies
A curiosity-driven mindset that stays current with ML research and brings practical insights to real-world engineering challenges

What the job involves

As a Machine Learning Engineer on the AI Models team at Tenstorrent, you’ll bring up and optimize cutting edge AI models to run on our custom AI devices
You’ll experiment, optimize, and push boundaries while solving real world problems
What You Will Learn:
How to get real ML models to fly on a custom AI accelerator
Ways to optimize ML model performance, from application to silicon level
What it takes to go from research paper to production ready ML deployment
How to work alongside compiler, kernel, and hardware teams to drive new features, performance optimizations, and fixes

Our take

Tenstorrent is a US- and Canada-based semiconductor startup specializing in processors for AI workloads. Rather than building gneral-purpose CPUs or GPus, the company develops custom chips and sofrware optimized for running moder AI models. As demand for AI accelerates, and as a global chip shortage reshapes the semiconductor industry, these trends have become strong tailwinds for Tenstorrent.

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 specialized 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

$693m

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.

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