ML Infrastructure Engineer

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.

SUMMARY

We are seeking a Senior Machine Learning Infrastructure Engineer to join our team. The person who fills this role will design, build, and scale infrastructure to power massive-scale data, modeling, and analysis platforms, playing a critical role in shaping a high-performance, production-grade ML ecosystem to support rapid experimentation with diverse datasets spanning neural signals, behavior, and more. This person will have significant ownership over the ML R&D platform, working closely with domain experts to architect new cloud infrastructure, data pipelines, and modeling flows. The work will ultimately enable the development of cutting-edge models for neuroscientific discovery and neural decoding, empowering brain-computer interface technology to improve the lives of patients living with severe neurological conditions.

PRIMARY ROLE AND RESPONSIBILITIES

Create flexible and performant ML infrastructure

Design and build systems ML cloud infrastructure to enable massive-scale modeling and analytics

Support diverse model exploration, hyperparameter optimization, pretraining, fine-tuning, and evaluation processes

Design and optimize scalable distributed training pipelines, with support for features such model sharding, cross-GPU communication, and real-time training monitoring

Create, operate, and maintain robust ML platforms and services across the model lifecycle

Make informed architecture decisions that balance performance, cost, reliability, and scalability

Build diverse and scalable data platforms

Design, build, and optimize massive-scale databases and data pipelines for scalable, flexible, and reliable data access

Explore research-driven, tailored data solutions using existing and simulated data, comparing performance and efficiency across solutions for typical data-access patterns

Create infrastructure and pipelines for ingesting internal and external datasets with varied shapes, formats, and associated metadata

Design and assess custom data formats for efficient storage and slicing of high-dimensional time-series data

Enable efficient data movement, preprocessing, and artifact management for data lineage and modeling reproducibility

Meet company standards for delivered solutions

Establish best practices for reliability, observability, reproducibility, and operational excellence across the ML ecosystem

Make informed and collaborative decisions with domain experts across the software & ML teams

Foster visibility and reproducibility within the company by maintaining extensive documentation of design decisions, evaluations of viable alternatives for selected solutions, pipeline assessments, etc.

Support ML R&D operations while preparing for eventual incorporation into product pipelines

QUALIFICATIONS

Bachelor's degree in Computer Science, Electrical Engineering, or a related technical discipline

5+ years of industry experience in software engineering, large-scale data infrastructure, or systems ML

Extensive proficiency in Python

Familiarity with PyTorch

Experience designing, building, and maintaining high-throughput data pipelines for large and diverse datasets

Experience working with distributed-training frameworks (e.g. FSDP, DeepSpeed, Megatron-LM, Ray, etc.)

Experience building or optimizing ML training pipelines for transformers or other large neural-network models

Demonstrated ability to partner closely with research and modeling teams to productionize workflows

Excellent communication and collaboration skills to work effectively on cross-functional and interdisciplinary teams

Experience having technical ownership over at least one successfully implemented collaborative project

OTHER QUALIFICATIONS

Advanced degree (MS or PhD) in Computer Science, Electrical Engineering, or a related technical discipline

Proficiency in C++, Go, CUDA, Rust, and/or Java

Experience in data engineering and systems ML for time-series data

Deep understanding of the fundamentals of distributed systems, including scalability, fault tolerance, monitoring, observability, scheduling, performance tuning, and resource management

Experience with cloud-native environments and orchestration (Kubernetes, Docker, etc.)

Experience scaling foundation-model training infrastructure or multi-cluster computing environments

What We Offer

An opportunity to work on exciting, cutting-edge projects to transform patients’ lives in a highly collaborative work environment.

Competitive compensation, including stock options.

Comprehensive benefits package.

401(k) program with matching contributions.

Equal Opportunity Employer

Echo Neurotechnologies is an Equal Opportunity Employer (EOE). We celebrate diversity and are committed to creating an inclusive environment for all employees.

Confidentiality

All applications will be treated confidentially. Applicants may be asked to sign an NDA after the initial stages of the interview process.