Machine Learning Engineer

R&D      ·        Salt Lake City, UT      ·       Full time

Description

About Epitel:  Epitel is a venture-backed company empowering clinicians, patients, and caregivers who live with or care for neurological disorders. Epitel employs proprietary EEG wearables and powerful AI to create a new platform for brain diagnostics. Our system cuts the time to diagnose brain disorders from hours to minutes and solves critical care access issues. We’re building toward a continuous neurology care platform that will create novel biomarkers for neurological disorders. If you’re interested in a high-impact role at a neurology pioneer, this is it!

Role mission: This is an exciting opportunity to join Epitel’s expanding engineering team. In this capacity, you’ll heavily contribute to Epitel’s product vision of creating an end-to-end EEG platform to revolutionize neurology. Your primary aim will be focused on continuing the development and implementation of a seizure detection algorithm for our Remote EEG Monitoring system.

About the role:

In your first 30 days:

1. Understand the current state of seizure detection algorithms used by research and industry
2. Evaluate Epitel’s current REMI seizure detection algorithm
   1. Understand why and how the workflow was developed
   2. Understand the code base used

In your first 3 months:

1. Ownership and development of REMI seizure detection algorithm
   1. Develop a strategy and code base for seizure detection in REMI data
   2. Create and maintain quality documentation (ISO 62304)

In your first 6 months:

1. Implementation and deployment of algorithm inside AWS infrastructure
   1. Work with our DevOps consultant to implement the seizure detection in an off-line manner
2. Optimization and implementation of algorithm for use in real-time
   1. Consider methods to reduce complexity of algorithm that will allow for real-time detection of seizures for the in-hospital version of REMI.
3. Support RAQA with Quality and Regulatory testing and documentation

Role-based competencies:

• Machine Learning – Must have 3+ years of machine learning experience with preference towards Deep Learning frameworks and time series analysis of sensor data. This should be actual working experience in an industry job or research institution (e.g., graduate research). Recent undergraduates with strong academic experience and research-based experience will be considered.
• Programming – Must be skilled in Python based scientific programming and machine learning – e.g., Scikit-Learn, Numpy, Pandas, SciPy, Tensorflow, Keras, PyTorch, etc. Preference given to candidates with biological sensor/signal processing experience (e.g., MNE Python toolkits or EEGLab in Matlab).
• Deployment – Must be able to create production-ready code including configuration and test scripts.
• QMS – Must be able to document all aspects of the code-base and deployment in a clear and well-detailed manner following ISO 62304 standards.
• Biological Signal Processing – Preference to candidates that understand what makes biological signals, and more specifically their processing needs, different from other time series data.
• AWS – Preference given to candidates with AWS serverless deployment experience.
• Start-up Experience – We are a small and growing company and many work with minimal oversight.

Benefits

• Remote-friendly – we’re open to the best candidate anywhere in the US. To that end, we provide a stipend for remote work site of your choice (e.g., WeWork, Industrious) and WFH gear (e.g., keyboard, mouse, camera, etc.)
• Equity – every employee shares in Epitel’s success.
• Professional development allowance – we do better when you do better
• Medical/dental coverage – we pay 100% of premiums
• 401k contribution
• Unlimited vacation – we also take typical US holidays + Pioneer Day (harkening to our Utah roots!)
• Regular IRL meetings – remote work is convenient, but it’s important to get to know one another in-person. We organize time for us to all to be physically in the same place (as long as we’re all safe) every once in a while.