At Groq. We believe in an AI economy powered by human agency. We envision a world where AI is accessible to all, a world that demands processing power that is better, faster, and more affordable than is available today. AI applications are currently constrained by the limitations of the Graphics Processing Unit (GPU), a technology originally developed for the gaming market and soon to become the weakest link in the AI economy.

Enter Groq's LPU™ Inference Engine. Specifically engineered for the demands of large language models (LLMs), the Language Processing Unit outpaces the GPU in speed, power, efficiency, and cost-effectiveness. The quickest way to understand the opportunity is to watch the following talk – groq.link/scspdemo.

Why join Groq? AI will change humanity forever, and we believe preservation of human agency and self determination is only possible if AI is made affordably and universally accessible. Groq’s LPUs will power AI from an early stage, and you will get to leave your fingerprint on civilization.

Staff Machine Learning Software Engineer

About this role:

We seek exceptional machine learning developers/ engineers/researchers with experience developing machine learning models. As a part of the ML Systems team at Groq, you will work closely with Groq's sales, applications, and engineering teams to develop and optimize ML models and systems for our hardware and contribute to original research in the field.

Responsibilities & opportunities in this role:

Develop kernels and models (both customer and public domain models) for Groq hardware using low-level proprietary frameworks and popular higher-level machine learning frameworks. The models will span domains from machine learning (computer vision, natural language processing, recommendation engines, reinforcement learning) to high-performance computing (linear algebra)
Optimize models for Groq’s hardware by exploiting proprietary hardware features
Performance analysis of models on Groq hardware
Performance analysis of large-scale systems built using Groq hardware
Performance analysis of models on competitor hardware/systems
Contribute to driving features into Groq’s hardware based on model optimizations/insight
Publish research papers on ML model optimizations and hardware in top-tier ML conferences.

Ideal candidates have/are:

Analytical background with the ability to quickly understand complex hardware technologies, understand tradeoffs and build systems using them.
ML (Neural Networks) and math fundamentals expertise, with some experience/deep understanding in one or more of the following areas:
- Computer vision
- Natural Language Processing
- Recommendation engines
- Reinforcement Learning
- Linear algebra
Experience with a subset of the following:
- Python and C/C++
- TensorFlow, Pytorch, Caffe, or other ML Frameworks
- HW accelerator programming languages such as CUDA, MKLDNN
- Programming experience on other accelerators such as FPGAs or DSPs from evaluation to production.
Understanding of processor architectures and distributed systems and their implications on ML model performance
A strong writer and public speaker, I operate with integrity and drive transparency, openness, and effective communication.

Qualifications for this role:

Min MS in CS, CE/EE, Math, and Physics.
5 to 10 years of software and machine learning experience.
Recent Ph.D. computer science, math, or engineering graduates with ML experience will also be considered.
Publication record in ML conferences (ICML, NeurIPS, ICLR, CVPR) is a plus
Excellent leadership, mentoring, and cross-functional collaborative and influencing skills.
Effective communication & presentation skills
Able to work in a very dynamic start-up environment

Attributes of a Groqster:

Humility - Egos are checked at the door
Collaborative & Team Savvy - We make up the smartest person in the room, together
Growth & Giver Mindset - Learn it all versus know it all, we share knowledge generously
Curious & Innovative - Take a creative approach to projects, problems, and design
Passion, Grit, & Boldness - no limit thinking, fueling informed risk taking

If this sounds like you, we’d love to hear from you!

Compensation: At Groq, a competitive base salary is part of our comprehensive compensation package, which includes equity and benefits. For this role, the base salary range is $143,600 to $289,100, determined by your skills, qualifications, experience and internal benchmarks.

Location: Groq is a geo-agnostic company, meaning you work where you are. Exceptional candidates will thrive in asynchronous partnerships and remote collaboration methods. Some roles may require being located near our primary sites, as indicated in the job description.

At Groq: Our goal is to hire and promote an exceptional workforce as diverse as the global populations we serve. Groq is an equal opportunity employer committed to diversity, inclusion, and belonging in all aspects of our organization. We value and celebrate diversity in thought, beliefs, talent, expression, and backgrounds. We know that our individual differences make us better.

Groq is an Equal Opportunity Employer that is committed to inclusion and diversity. Qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, disability or protected veteran status. We also take affirmative action to offer employment opportunities to minorities, women, individuals with disabilities, and protected veterans.

Groq is committed to working with qualified individuals with physical or mental disabilities. Applicants who would like to contact us regarding the accessibility of our website or who need special assistance or a reasonable accommodation for any part of the application or hiring process may contact us at: hr@groq.com. This contact information is for accommodation requests only. Evaluation of requests for reasonable accommodations will be determined on a case-by-case basis. #LI-Remote

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