Algorithm and Machine Learning Engineer, Beacon Biosignals
More information about location
AI brain monitoring
Open for applications
AI brain monitoring
21-100 employees
Open for applications
More information about location
21-100 employees
Company mission
To improve human health by enabling rapid, targeted interventions through advanced brain analytics.
Role
Who you are
- You have more than 5 years of industry experience in machine learning and deep learning, particularly in health sciences or other regulated fields, with a proven track record of bringing algorithms into production
- You are experienced with digital signal processing (DSP) and statistics and care about using the right tool for the job, which in many cases might not be machine learning or deep learning
- You are proficient in using PyTorch (preferred) or other deep learning frameworks for training, developing, and deploying deep learning models
- You are proficient with latest Deep Learning advances (Transformer/ViT, large scale modeling, large model training, ...)
- You follow and spread best practices in software and ML engineering, including testing, version control, code reviews, documentation, Dockerization, CI/CD, and experiment tracking
- You are experienced with biosignals, medical imaging data, or large time-series datasets, or are enthusiastic about learning more in the domain
- You thrive in a team environment, recognizing that collaboration, open communication, and continuous feedback are essential for collective success
- You are able to distill, discuss, and present complex technical topics in a way that is appropriate for the audience at hand, both internally and externally
- You are excited to participate in the entire algorithm development lifecycle, which spans scoping, data wrangling, algorithm development/experimentation, formal validation, quality/regulatory documentation, production deployment, and working with clients who might benefit from these algorithms
What the job involves
- As part of Beacon's analytics and machine learning domain, you'll work alongside fellow data scientists, neuroscientists, engineers, and clinicians to scope, build, deploy, and maintain the machine and deep learning models that analyze brain and biosignal data for advancing sleep, neurological, and psychiatric therapy development
- Participate in and lead the entire biosignal-based algorithm development lifecycle for medical devices including specifications and requirements gathering, data curation and labeling, development, failure-analysis, production, maintenance, and documentation
- Select, implement, and develop the most appropriate method for each problem, knowing when to apply deep learning techniques and when other methods are more effective
- Enhance our internal deep learning and machine learning tools to boost team efficiency, introduce new model architectures and algorithmic techniques, and refine the codebase to encourage reusability where needed to enable rapid experimentation
- Spread and improve our best practices to ensure algorithm implementations are user-friendly, well-documented, and thoroughly tested, including unit tests, comprehensive documentation, CI, and non-regression testing
- Present results to key stakeholders and assist them in utilizing algorithms for client engagement
- Support the client-facing projects to understand and shape the impact Beacon algorithms have for our customers, both for existing deployed algorithms, and future algorithm development
Our take
The brain has long been considered one of the most mysterious fields of medicine - and psychiatric and neurological diseases therefore one of the least understood. Better access to real-time brain data, however, could change this. That’s exactly what Beacon Biosignals is hoping to deliver.
Beacon Biosignals has developed a scaleable electroencephalogram (EEG) analytics platform that leverages AI to more accurately and insightfully manage brain data. Its capabilities run from analysing existing data, to identifying and standardizing neorobiomarkers, to continuously aggregating and analyzing trial data.
The hope is that this will help clinical brain researchers carry out faster and more accurate work, ultimately accelerating the pace of treatment development in neurology. It’s a smart new AI application, and Beacon Biosignals is acquiring new companies to scale and receiving handsome funding - but for that reason the company isn’t alone in pursuing it. Bitbrain is also developing neurology AI, although with a tighter focus on product development. This may help differentiate Beacon Biosignals in what is still a relatively new market area.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 3 rounds)
Nov 2021
$27m
SERIES A
Jun 2019
$3m
SEED
Total funding: $30.5m
Company values
- The highest quality science is performed by teams. It's also more fun
- Successful product development requires rapid, early feedback from real patients and clinicians
- Feats of technical wizardry are only useful in combination with honest, frequent, and open communication
- A diverse team builds more robust systems and practices more impactful science
Company HQ
Beacon Hill, Boston, MA
Articles
Leadership
Jarrett Revels
(CTO)Previously a Software Engineer at MissionFocus, who then moved into various engineering and research roles at MIT.
Jacob Donoghue
(CEO)Completed a Neuroscience PhD at MIT, and received his MD from Harvard Medical School. Subsequently carried out research for Cyberkinetics Neurotechnology Systems and Massachusetts General Hospital.
Brandon Westover
(Co-founder)Received his MD from Washington University School of Medicine, then took up a Neurology residency at Harvard Medical School. Alongside his work at Beacon Biosignals, is also an HST Faculty member at MIT and a Neurologist/Medical AI Researcher at Massachusetts General Hospital.
Syd Cash
(Co-founder)An Associate Professor at Harvard Medical School, who also leads the Center for Neurotechnology and Neurorecovery at MGH.
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