4 дня назад
Machine Learning Engineer (Brain-Computer Interface)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Machine Learning Engineer (Brain-Computer Interface) (Python/ML): Developing and deploying machine learning models and sensing systems for wearable devices using time-series data, with an accent on advanced ML techniques, physiological signals, and real-time sensor systems. Focus on designing training and evaluation tools, integrating algorithms across hardware and software teams, and solving complex engineering challenges for brain-computer interface applications.
Location: Paris, France; office attendance expected 4+ days per week
Company
is a technology company developing chat, Specs augmented-reality eyewear, OS, Lens Studio, Bitmoji, and other digital services.
What you will do
- Design, implement, and deploy machine learning models and systems for wearable device sensing.
- Develop machine learning solutions for time-series data within the Brain-Computer Interface team.
- Collaborate with software, research, hardware, and international Specs teams to deploy algorithms and resolve integration issues.
- Build tools for training, testing, and evaluating machine learning performance.
- Write clean, tested code and communicate technical trade-offs through design documents and reviews.
Requirements
- Master’s degree in Machine Learning, Computer Science, or an equivalent field.
- 3+ years of research or engineering experience with machine learning approaches.
- Strong knowledge of Python or C++ and deep understanding of machine learning principles, algorithms, and systems.
- Experience with machine learning frameworks such as PyTorch and MLflow, cloud environments including Google Cloud or AWS, Git, and code reviews.
- Fluency in English is required.
- Ability to debug and improve existing code, develop algorithms using advanced time-series techniques, and explain complex ideas clearly.
Nice to have
- PhD in Machine Learning, Computer Science, or an equivalent field.
- Expertise in digital signal processing, time series, EEG, or other physiological sensor data.
- Experience with real-time machine learning, sensor systems, continuous integration, and code quality tools.
- Experience developing AI agentic tools for engineering workflows and machine learning experimentation.
Culture & Benefits
- Default-together working approach with in-office collaboration expected 4+ days per week.
- Collaboration with hardware and software teams around the world.
- Paid parental leave and comprehensive medical coverage.
- Emotional and mental health support programs.
- Compensation packages that support participation in ’s long-term success.
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