Research Engineer

About the role

Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together.

The Company operates Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services.

Specs Inc. is a wholly-owned subsidiary of Snap Inc. dedicated to making computing more human. The company develops Specs, advanced eyewear that seamlessly integrates digital experiences into the physical world. Specs feature see-through lenses that place digital objects directly into three-dimensional space, powered by Snap OS, a proprietary, context-aware operating system designed for natural interaction with your hands and voice.

Specs Inc. also provides Lens Studio, a full suite of advanced developer tools that powers immersive augmented reality experiences across Specs, Snapchat, and other services. We’re looking for a Research Engineer to join the Spectacles BCI Team at Snap Inc.!

In this role, you will be working on the state of the art of machine learning (ML) for time series data, developing the next generation of wearable device sensing. Working from our Paris office (9th arrondissement), you will be collaborating closely with other Specs hardware and software teams around the world.

What you’ll do:

- Conduct focused, product-related research projects, defining hypotheses and designing experiments using electrophysiological and cognitive data.

- Review relevant literature and translate scientific knowledge into modeling approaches aligned with product needs.

- Build signal-processing and ML pipelines for noisy, real-world time-series sensor data.

- Develop algorithms and ML models for cognitive and physiological decoding using multimodal biological signals captured via wearable devices..

- Collaborate with software and research teams on model development and evaluation, data capture and demos.

- Translate findings into clear recommendations for stakeholders and leadership.

Knowledge, Skills & Abilities:

- Strong signal-processing fundamentals applied to noisy, real-world biosensor data.

- Proficiency in Python and experience with scientific-computing and ML tools.

- Working knowledge of ML for multivariate time series and multimodal sensor fusion.

- Ability to turn research or product questions into concrete technical plans, experiments, metrics, and deliverables.

- Ability to clearly communicate model limitations, uncertainty, and technical tradeoffs clearly to cross-functional partners.

- Familiarity with AI-assisted engineering workflows.

Minimum Qualifications: