Senior Machine Learning Infrastructure Engineer

Join a Leading well-funded technology start-up focusing on the development of bleeding-edge integrated circuits and systems for agentic AI, such as Large Language Models.

As a Machine Learning Infrastructure Engineer, you will play a crucial role in developing a robust framework for rapid training and experimentation of large language models. Your responsibilities will include architecting an internal platform to facilitate high-throughput inference of these models. You will develop the core inference engine to seamlessly deploy large machine learning models to customers at scale and across distributed systems, contributing significantly to the automated pipeline, optimizing for high throughput training runs and rapid experimentation while achieving top hardware efficiency.

Qualifications:

We are seeking candidates with exceptional ML engineering evidenced by:

• Experience in creating and managing high-performance computing clusters across GPU/TPU, preferably in PyTorch.
• Proficiency in efficient serving of large machine learning models at scale, including quantization and distributed computing, leveraging libraries such as deepspeed.
• Strong software engineering acumen with expertise in software design/architecture, particularly in Python.
• Understanding of the latest AI research and ability to efficiently implement these systems.
• Prior experience at a leading machine learning company (OpenAI, DeepMind, Meta, Anthropic, HuggingFace, etc.).

Nice to Have:

• Experience as an early engineer at a fast-growing startup.
• Interest in and consideration of the impacts of AI technology.

Key Words: Machine Learning / LLM / Large Language Model / PyTorch / High Performance Computing / HPC / GPU / TPU / Deepspeed / AI / OpenAI / Distributed Systems

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