Algorithm Engineer

Beacon; Paris; Hybride; EUR 85 000 - 110 000; Plein temps

Avantages offerts par ce poste

Equity

Paid time off

Remote-friendly

Résumé du poste

Beacon Biosignals in Paris (hybrid) is seeking a Machine Learning Engineer to join our analytics domain and help scope, build, deploy, and maintain models that analyze brain and biosignal data for sleep, neurology, and psychiatry therapy development.

You will work with data scientists, neuroscientists, engineers, and clinicians to implement methods, ensure tests and documentation, and present results to clients and stakeholders.

Qualifications

• 4+ years of industry experience in machine learning and deep learning, in health sciences or other regulated fields.
• Proficient in DSP and statistics; choose right tool for the job.
• Proficient in PyTorch or other DL frameworks for training, developing and deploying models.
• Familiar with latest DL advances (Transformers/ViT, large-scale modelling).
• Follow best practices in software and ML engineering: testing, version control, code reviews, documentation, Dockerization, CI/CD, experiment tracking.
• Familiar with biosignals, medical imaging data, or large time-series datasets.

Responsabilités

• Lead and contribute to the entire biosignal-based algorithm development lifecycle for medical devices (specifications, data labeling, development, production, maintenance).
• Select and develop appropriate methods for each problem, applying DL when suitable.
• Enhance internal ML tools, introduce new architectures, and promote reusable code for rapid experimentation.
• Ensure algorithms are user-friendly, well-documented, tested, and covered by CI/non-regression tests.
• Present results to stakeholders and support client engagement with deployed and future algorithms.
• Collaborate with clients to understand impact of Beacon algorithms on their projects.

Connaissances

Machine Learning

Deep Learning

DSP

Statistics

PyTorch

Transformers

Software Engineering

CI/CD

Docker

Experiment Tracking

Time-series

Outils

Git

Docker

CI/CD Pipelines

Description du poste

Beacon Biosignals is transforming precision medicine for the brain, from clinical development to clinical care. For Life Sciences partners, we offer the leading at-home EEG platform for clinical development of novel therapeutics for neurological, psychiatric, and sleep disorders. Our Diagnostics business is building the most comprehensive at-home platform for precision diagnostics, combining EEG and cardiopulmonary signals to deliver reimbursable assessments for sleep and central nervous system disorders. Together, we're changing the way patients are diagnosed and treated for any disorder that affects brain physiology.

Beacon Biosignals is seeking a Machine Learning engineer!

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.

At Beacon, we've found that cultural and scientific impact is driven most by those who lead by example. As such, we're always seeking out new contributors whose work demonstrates innate curiosity, a bias toward simplicity, an eye for composability, a self-service mindset, and—most of all—a deep empathy toward colleagues, stakeholders, users, and patients. We believe a diverse team builds more robust systems and achieves higher impact.

Beacon's robust asynchronous work practices ensure a first-class remote work experience, but we also have in-person office hubs in Boston, New York City and Paris.

What success looks like

• 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.

What you will bring

• You have more than 4 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 familiar with latest Deep Learning advances (Transformer/ViT, large scale modeling, large model training, ...)
• You follow and adopt best practices in software and ML engineering, including testing, version control, code reviews, documentation, Dockerization, CI/CD, and experiment tracking.
• You are familiar 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.

The base salary range for this role is determined based on past experience, specific skills and qualifications. The base salary is one component of the total compensation package, which includes equity, PTO and other benefits.

At Beacon, we've found that cultural and scientific impact is driven most by those that lead by example. As such, we're always seeking new contributors whose work demonstrates an avid curiosity, a bias towards simplicity, an eye for composability, a self-service mindset, and - most of all - a deep empathy towards colleagues, stakeholders, users, and patients. We believe a diverse team builds more robust systems and achieves higher impact.