Research Engineer - Time-Series ML for Wearable Biosensors

SNAP, Inc.; Paris; On-site; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Paid parental leave

Comprehensive medical coverage

Emotional and mental health support

Long-term incentive equity

Job summary

Snap Inc. in Paris is seeking a Research Engineer to advance ML for time-series data from wearable devices.

You will build signal-processing and ML pipelines, develop decoding models, and collaborate across hardware and software teams to deliver practical, data-driven insights for Spectacles hardware and related services. The role requires a strong background in signal processing, Python, and multimodal data, with 3+ years of relevant work and a Master’s degree (PhD preferred).

Qualifications

• Master's degree in ML, CS, biomedical engineering, or related field.
• 3+ years of research or engineering experience with time-series, biometric or multimodal data.
• Hands-on experience with wearable biometrics products or platforms.

Responsibilities

• Conduct focused, product-related research projects, defining hypotheses and experiments with electrophysiological and cognitive data.
• Review literature and translate science into modeling approaches aligned with product needs.
• Build signal-processing and ML pipelines for noisy time-series sensor data.
• Develop algorithms and ML models for cognitive and physiological decoding using multimodal signals.
• Collaborate with software and research teams on model development, data capture and demos.
• Translate findings into clear recommendations for stakeholders and leadership.

Skills

Signal processing

Python

Time-series ML

Multimodal fusion

Technical planning

Model limitations communication

AI-assisted workflows

Education

Master’s degree in ML/CS/Biomedical engineering

PhD in related field (preferred)

Job description

Snap Inc. in Paris is seeking a Research Engineer to advance ML for time-series data from wearable devices.

You will build signal-processing and ML pipelines, develop decoding models, and collaborate across hardware and software teams to deliver practical, data-driven insights for Spectacles hardware and related services. The role requires a strong background in signal processing, Python, and multimodal data, with 3+ years of relevant work and a Master’s degree (PhD preferred).