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Snap

Research Engineer

  • Office
  • 3-6 years

Salary

Not stated

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Description

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.

Responsibilities

  • 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:
  • Master’s degree in machine learning, computer science, biomedical engineering, computational neuroscience or related fields.
  • 3+ years of relevant research or engineering experience developing algorithms or models for time series, biometric, physiological, wearable, behavioral, or multimodal data.
  • Hands-on experience with wearable biometrics products or platforms, such as smartwatches, fitness trackers, health trackers, sports-performance wearables, or similar real-world sensing devices.
  • Preferred Qualifications:
  • PhD in biomedical engineering, computational neuroscience, signal processing with a focus on biosignals or an equivalent record of applied research and engineering impact.
  • Experience in electroencephalography, Brain-Computer Interface or cognitive-state estimation.
  • Experience designing ML systems for multivariate time series, representation learning, calibration, or domain adaptation.
  • Experience with artifact-aware modeling, noisy labels or physiological proxy labels.
  • Experience deploying or optimizing ML models for real-life environments
  • Experience with agentic AI workflows, skills-based automation, or AI-assisted research.
  • If you have a disability or special need that requires accommodation, please don’t be shy and provide us some information .
  • "Default Together" Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a “default together” approach and expect our team members to work in an office 4+ days per week.
  • At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets.
  • Our Benefits : Snap Inc. is its own community, so we’ve got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap’s long-term success!

Where you’d work

From the office

About the company

Snap

Office in Paris, France

Also hiring in Los Angeles, United States, Seattle, United States, San Francisco, United States and 13 more places

2 of their 84 open roles are remote

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  • Must-haves
Details10 facts · Role, Location, Compensation, Employment
Tech stack
  • Python
Type
Full-time
Specialty
ML
Region
Europe
Pay period
Annual
Show 5 more factsShow less

Role

Category
Data & Analytics
Specialty
ML
Experience
3+ years
Tech stack
  • Python

Location

Work model
Office
Region
Europe
Office
  • Paris, France

Compensation

Salary
Salary by agreement
Pay period
Annual

Employment

Type
Full-time

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