Lead ML Research Engineer (LLMs, Quantization, Inference)
Lead ML Research Engineer (LLMs, Quantization, Inference)
We are seeking a Lead Machine Learning Engineer with a strong focus on systems to drive the development of next-generation computing solutions.
This role is ideal for a dynamic professional who thrives under pressure, utilizing their deep expertise in machine learning and systems integration to significantly enhance computational performance and efficiency.
Our company is at the cutting edge of developing a highly integrated chip and software stack designed for advanced computing applications, including the potential to support artificial general intelligence (AGI) in the future.
Our goal is to deliver a platform that significantly outstrips current benchmarks in cost-effectiveness and performance, setting new standards for computational efficiency.
In this crucial role, you will lead efforts to train and optimize large language models (LLMs) tailored for our innovative hardware.
Your focus will be on creating distributed systems for effective training and inference, ensuring that our solutions deliver a dramatic increase in performance-per-dollar, substantially exceeding typical industry advancements.
What We Offer :
- Competitive salary and significant equity in a pioneering company.
- Customized benefits package to meet your needs.
- A dynamic and supportive work environment that encourages innovation and collaboration.
- Opportunities for professional growth in a rapidly advancing field.
Key Responsibilities :
- Optimize LLMs to maximize the performance capabilities of our specialized hardware.
- Conduct thorough quality evaluations to ensure superior performance standards.
- Develop and manage scalable distributed systems for efficient training and inference processes.
- Provide expertise in hardware architecture to enhance machine learning efficiency and effectiveness, ensuring optimal performance.
Relevant Keywords : Machine Learning, Large Language Models, Next-Generation Computing, Systems Integration, Distributed Infrastructure, Hardware Optimization, Neural Network Training.
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