Machine Learning Software Engineer Intern, Groq
The US pay range for our technical internships is $30-$50 / per hour
More information about location
AI semiconductor chip manufacturer
Be an early applicant
AI semiconductor chip manufacturer
201-500 employees
Be an early applicant
The US pay range for our technical internships is $30-$50 / per hour
More information about location
201-500 employees
Company mission
To increase developer velocity in machine learning by leading the way with simple, fast, innovative solutions.
Role
Who you are
- To succeed in this role, you will need to bring a deep understanding of ML model architecture, as well as the ability to recognize effective partitioning strategies and custom model-level optimizations that can unlock the potential of Groq's LPU system
- Strong understanding of transformer-based multimodal LLM architectures (e.g Llama, Mixtral, Pixtral) and common machine learning operators and techniques (e.g. Attention, Cross-attention, Embeddings, Tokenization, Quantization)
- High proficiency in Python, particularly in PyTorch in the context of machine learning models
- Familiarity with huggingface and experience with quality evaluation of multimodal LLMs
- Experience with Linux-based development environments and ability to work comfortably in a terminal-based environment
- Familiarity with Test-Driven Development principles and practices, including writing unit tests and integrating testing frameworks
- Ability to write clear, concise, and well-documented code, and to collaborate with others to ensure high-quality software development
- Knowledge of Rust and C++ is a plus, as is familiarity with MLIR, LLVM, ONNX and distributed systems (MPI)
- Must be authorized to work in the United States or Canada
What the job involves
- Groq's Summer Internship Program runs from May - September and is full-time during the duration of the internship
- As a member of our Multimodality team, you will play a key role in driving the launch of the latest models that process and generate audio, image, and video content
- Our team operates at the intersection of Machine Learning Models, Groq's Inference Engine, and Groq's Compiler, with a mission to expand Groq's model portfolio and demonstrate the universality of our architecture and the maturity of our software stack
- Additionally, you will be responsible for ensuring state-of-the-art quality of our deployments, including verifying that quantization or other precision-affecting changes have minimal impact on evaluation scores
- You will collaborate closely with multiple teams, including the Compiler team, the Hardware team, and the System Software team, as well as our product and strategy leadership, to ensure the successful launch of new models
- Implement optimizations and decompositions at the PyTorch level while working with the latest machine learning models across research and industry
- Coordinate with the compiler team to compile model partitions to executables to be run on Groq's LPU systems and enable further model-specific optimizations
- Implement orchestration software to run compute pipelines on large systems of hardware, enabling blazing-fast inference
- Develop profiling tools to understand bottlenecks across the runtime stack and drive improvement based on rigorous metrics that customers and developers care about
Our take
Groq is an exciting semiconductor startup focused on creating advanced chips designed specifically for AI applications, particularly for AI inference, where models use trained data to deliver fast responses.
Groq aims to challenge Nvidia's dominance by focusing on speed and efficiency for AI deployment. While Nvidia's GPUs handle both training and running AI models, Groq's LPUs are optimized for inference tasks. With a recent $640M funding round, Groq plans to scale up and deploy over 100,000 LPUs by 2025.
To achieve this, the company has partnered with companies like Meta and Samsung, as well as sovereign entities like Saudi Aramco, showcasing the company's growth and potential. With its exciting technology, Groq is well-positioned to play a significant role in the AI chip market in the coming years.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 5 rounds)
Aug 2024
$640m
SERIES D
Jul 2024
$300m
SERIES D
Total funding: $1.3bn
Company HQ
Old Mountain View, Mountain View, CA
Articles
Leadership
Jonathan Ross
(Founder & CEO)Majored in Mathematics and Computer Science at NYU. Joined Google as a Software Engineer in 2011, and was promoted to Hardware Engineer in 2013. Co-founded Google's Tensor Processing Unit. Was also a Rapid Evaluator at Google X, and then founded Groq in 2016, acting as its CTO before becoming the CEO in 2018.
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