Machine Learning Engineering Lead

About the role

Company Overview

Echo Neurotechnologies is an exciting new startup in the Brain-Computer Interface (BCI) space, driving innovation through advanced hardware engineering and AI solutions. Our mission is to deliver cutting-edge technologies that restore autonomy to people living with disabilities and improve their quality of life.

Team Culture

Join a small, dedicated team of knowledgeable and motivated professionals. Our early-stage environment offers the opportunity to take ownership of broad decisions with significant and long-lasting impact. We emphasize continuous learning and growth, fostering cross-functional collaboration where your contributions are vital to our success.

Job Description

We are seeking a Machine Learning Engineering Lead to design, scale, and deploy clinical-grade ML algorithms in the cloud. In this role, you will initially operate as a high-impact individual contributor, and as the platform matures, you will expand and lead a dedicated team of machine learning engineers, shaping both the technical roadmap and day-to-day execution. You will take ownership of translating complex, neurophysiological signals into production-ready predictive models and automated diagnostic features. You will design, build and deploy cloud-based models, ensuring data is processed with high reliability, low latency, and strict regulatory compliance.

Role Responsibilities

- Algorithm Productionization & Cloud Deployment: Design, build, and deploy scalable ML pipelines and clinical algorithms in the cloud to process real-time and batch neural and contextual data.

- Model Optimization & Validation: Train, evaluate, and optimize machine learning models for signal processing, feature extraction, and behavior detection while maintaining high sensitivity and specificity.

- Model Deployment & Pipeline Integration: Architect scalable pipelines to deploy and integrate production models into the cloud environment, managing model automated training, data versioning, and performance monitoring, in collaboration with a platform team.

- Mentorship & Process: Introduce engineering best practices, including CI/CD pipelines, code reviews, and modular architecture, while coaching and mentoring engineers through regular feedback and technical guidance.

- Team Growth & Leadership: Build and scale a high-performing ML engineering team from the ground up, transitioning into a direct line management role to lead technical strategy, resource planning, and day-to-day execution.

- Quality & Regulatory Compliance: Produce rigorous technical documentation, software design specifications, risk analyses, and validation protocols to support regulatory submissions under strict quality management systems.

Role Qualifications

Required Qualifications

- Bachelor’s or Master’s degree in Computer Science, Data Science, Biomedical Engineering, or equivalent practical experience.

- 5+ years of software engineering experience focusing on building, deploying, and maintaining production machine learning models in cloud environments.