Machine Learning engineer - Seattle, WA, United States - SuperMoney, LLC.

Description

Semiconductor chips are the driving force behind the modern technology-driven world.

They power everything from cars to rockets, sensors to servers, and have a crucial role to play in several major industries, making the $1T semiconductor industry a vital component of the global economy.

However, designing modern semiconductor chips is a costly, engineering-intensive process, further worsened with archaic tools.

With a growing number of organizations designing their own chips and the rising consumption of semiconductors in day-to-day life, the work you will do will significantly impact the lives of many.

We are super excited about what we are building; We are looking for an exceptional Applied Research Engineer to join our founding team and contribute to improving our in-house large language models (LLMs).

In this role, you will apply cutting-edge techniques to fine-tune LLMs and implement novel ways to improve their performance on our target applications.

Several years of full-time experience in applied ML roles, preferably in a fast-paced environment like early-stage startups.
Detail oriented and a strong desire to build high-quality customer-focused products
Strong basics and understanding of Machine Learning/Deep Learning
Experience in building diverse and high-quality datasets and training deep learning models
Strong programming skills in Python
Familiarity with deep learning frameworks such as TensorFlow or PyTorch
Prior experience in fine-tuning large language models desirable
Experience setting up infrastructure for training large deep-learning models

We are a small but passionate group with a mission to dramatically reduce the time, cost, and engineering effort needed to build complex silicon chips.

Our founding team comprises of experts in chip design, AI, and modern software stacks. In past lives—we were researchers, engineers, and leaders at major chip design/AI companies like Qualcomm, Nvidia, Facebook, Google, etc. research institutions.

As a funded startup, we also have several unique benefits that you can't really get anywhere else:

Access to unique learning opportunities — With the Allen Institute for AI (AI2) as a co-founder, our team gets access to numerous talks by leading AI researchers/paper authors, knowledge sharing amongst the community of hundreds of engineers working for AI2 companies, and much more.

As a part of the multi-disciplinary team, you get to interact with people from very different backgrounds (from chip design to AI to software engineers).

Early-stage equity — Early-stage risk comes with early-stage equity for you. ChipStack focuses on Semiconductors and Artificial Intelligence. You can view their website at
#