About the job
Echo Neurotechnologies is a dynamic startup revolutionizing the Brain-Computer Interface (BCI) sector. We are committed to creating innovative hardware solutions powered by artificial intelligence, with the goal of enhancing the lives of individuals with disabilities and promoting independence through advanced technology.
Team Culture
Become part of a close-knit group of passionate professionals in a fast-paced environment. As part of our early-stage team, you will have the chance to influence important decisions that yield substantial, lasting results. We prioritize continuous learning and collaboration, ensuring your contributions are integral to our collective success.
Job Summary
We are on the lookout for a Senior Machine Learning Infrastructure Engineer to join our talented team. In this pivotal role, you will be responsible for designing, constructing, and scaling infrastructure that supports large-scale data processing, modeling, and analysis. You will play an essential role in developing a high-performance, production-ready ML ecosystem that facilitates swift experimentation across diverse datasets, including neural signals and behavioral data. You'll have substantial ownership of our ML R&D platform, collaborating closely with domain experts to develop new cloud infrastructure, data pipelines, and modeling workflows, ultimately leading to the creation of state-of-the-art models for neuroscientific breakthroughs and neural decoding, thereby improving the lives of patients with severe neurological disorders.
Key Responsibilities
Create adaptable and efficient ML infrastructure:
- Design and implement ML cloud infrastructure for extensive modeling and analytics.
- Facilitate diverse model exploration, hyperparameter tuning, pretraining, fine-tuning, and evaluation.
- Develop and refine scalable distributed training pipelines, incorporating model sharding, cross-GPU communication, and real-time training monitoring.
- Manage and sustain robust ML platforms and services throughout the model lifecycle.
- Make strategic architecture decisions balancing performance, cost, reliability, and scalability.
Build flexible and scalable data platforms:
- Design and optimize large-scale databases and data pipelines to ensure reliable data access.

