Backend Software Engineer, New Grad
We have an immediate opening for a recent college graduate with an affinity for backend development and an interest in machine learning to join a growing team of developers, researchers, and medical professionals.
The ideal candidate is excited by the idea of developing and architecting solutions in a variety of different environments and problem domains and is interested in being an essential part of a team.
Developing and architecting extensible, robust, and efficient backend solutions with a small team of developers.
Rapidly learning and adapting to new programming languages, technologies, and projects.
This is primarily a software engineering role (80% of your time). You think in terms of micro services and APIs and will work towards building out new backend features and evolving our codebase towards improved reliability and observability.
This role also requires a strong systems engineering background (e.g. bash scripting, Unix-based systems, troubleshooting network/database performance issues, logging, init systems, chroot/containers; 20% of your time).
You will ultimately own the backend and infrastructure of our systems-- identify and resolve performance bottlenecks, design and build out new features and services, automate provisioning of new micro services.
You must have experience with software development in Python (i.e. beyond just scripting and data analysis/visualization using Python).
You must have experience working in a Linux environment (e.g. bash scripting, init and logging systems, configuring web and database services).
You should have experience with web applications, databases, Git in a team environment, monitoring/logging systems.
You should have a passion for continued learning to improve your skills and those around you.
Experience with C++11/C++14/C++17.
Experience in a JVM language.
Experience with writing multi-threading software.
Electronics and hardware tinkering experience.
Embedded systems experience (deployment into low resource and offline environments, interaction with hardware through code, signal processing of analog and digital signals).
Android filesystems experience (e.g. Android shell, adb).
Research Engineer: Signal Processing, Machine Learning, EEG Analysis
The position involves developing machine learning algorithms for innovative biomedical technologies involving physiological signal processing. The successful candidate will work closely with a team of physicians, nurses, engineers, and scientists in designing new medical technologies for the intensive care unit.
Candidates with experience in the analysis of experimental data derived from---but not limited to---auditory/visual/cross-sensory psychophysical, EEG, ECG, and galvanic-skin conductance, data would be given a higher priority.
MS in electrical engineering or biomedical engineering or a similar discipline.
Expertise and innovation in methods, theory, and application of machine learning and data mining with a broad understanding of methodological approaches and proficiency in practice.
Expert abilities to work with new data sets regardless of prior exposure to current topic.
Strong interest in research and learning new technologies.
Experience with Python.
Collaborate with a team of machine learning, control engineering, and signal processing researchers.
Provide technical expertise to address supervised and unsupervised learning problems in an applied research environment.
Develop and deploy modern machine learning and statistical methods for finding patterns and models from physiological data.
Prior expertise and exposure using non-invasive human physiological measures such as EEG, ECG, galvanic-skin conductance, or other categorically similar methodologies.
Prior experience in feature extraction from physiological signals.
Experience working with quantitative methods of neural data analysis.