View Open Roles


View Open Roles


View Open Roles

Mission Driven

Driver is dedicated to making life-saving driving technology available to everyone. We all have our tales from the road–the near misses and collisions that shake us to our core and reshape the fabric of our lives. We’re excited to see advancements in automotive technology make our commutes safer, but we don’t believe these benefits should be awarded only to those who can afford a high-end Tesla or Porsche. At Driver, we’re leveraging the power of computer vision and big data analysis to make collision alerts and driver assistance features available on common mobile devices. We also work with some of the largest autonomous vehicle companies in the industry to make self-driving cars safer. These challenging tasks are the beating heart of Driver’s product culture.

Big data

When we say big data we mean it. Every month, we collect over 250k miles of drive data (a trip to the moon), 100M drive images, and billions of telematics events. We’re working at a scale that provides unique insights into real world driving behavior in every country and city in the world. We take serious responsibility for this data, and care deeply about the privacy of our users — our data processing pipeline starts with anonymization and obfuscation steps to ensure that drivers can use our app with confidence.

Automotive innovation

Scale isn’t the only challenge at Driver. Whether you’re a scientist or a hacker, a people person or a product guru, we’re solving questions that can’t be found on Stack Overflow. Our MADAS (“mobile” advanced driver assistance system) builds a behavioral model for driving that adapts to local norms and ensures that everyone stays safe, whether you’re cruising the streets of Santa Cruz, Caracas, or Cluj.

Remote teamwork

Driver is committed to creating a kind, inclusive, and family friendly working environment. We believe in building a global community of thinkers and tinkerers. Our team hails from both US coasts, Canada, Italy, Pakistan, China, and Russia. Great problems know no bounds, so neither can great solutions. We’ve come together at Driver to do the best work of our careers; to write and ship elegant code; to make pixel perfect designs; and to literally save lives. We’d love for you to join us on this journey.

Available Roles

Software Engineer (Android)

Our Engineering Culture

  • We are passionate about our products and road safety.
  • We believe that software should be available to everyone, not just folks with the latest hot devices. Driver is an international and equality focused product, which means coding for the lowest common denominator of technology available in the developing world.
  • We enjoy wearing many hats. One day you may be working on acceleration data processing and the next an exciting user-facing feature.
  • We are automated-testing-oriented, but take a pragmatic approach to make sure our tests provide a meaningful impact. In other words, high code coverage is great, but increasing a number is not the only goal.
  • We are diverse, smart, and focused, but don’t take ourselves too seriously.
  • All remote and global team!



  • Experience building beautifully factored, high performance Android apps.
  • Participate in code review and perform extensive testing to ensure we deliver high quality software.
  • You’re excited about using low level motion APIs (accelerometer, gyroscope, etc.) to develop behavioral models for safe driving behavior.
  • You’re well-versed in Kotlin.
  • You are comfortable methodically breaking large projects down into smaller parts and collaborating with the team along the way.
  • Research new technology and tools and share those findings with the team.
  • You care deeply about the user experience.
  • You don’t believe in simply accepting performance tradeoffs on resource-limited devices – optimizing CPU, network use, and battery life gets you excited.
  • You think code without unit or UI tests isn’t finished code, full stop. S.O.L.I.D. is your car’s vanity license plate.
  • You’re a tinkerer and the idea of working with computer vision on the mobile edge using Tensorflow Lite is exciting.


Nice To Haves

    • Experience with Jetpack (flow, compose, work manager, room, etc.).
    • Experience with or an understanding of newer approaches to networking, like GraphQL.
    • Experience with iOS/Swift.
    • Familiarity with CI/CD systems.
    • Familiarity with scalable automated testing on real devices (e.g. device farm testing).
    • Familiarity with computer vision / machine learning on Android (e.g. tensorflow lite).
    • Familiarity with trunk based development and release trains.

Platform Engineer

  • You have 5+ years of experience building scalable microservices.
  • You have strong server-side experience, particularly with languages such as Node.js, Elixir, Ruby, or Python and relational/non-relational databases (i.e. RDBMS, Columnar, and Key-Value stores)
  • You’ve worked with real-time, near-real-time, and batch-oriented data processing systems. You have opinions about queues, exchanges, pub/sub architecture, and stateless workers.
  • You’re equally comfortable sharding TB scale databases, writing application code for massively parallel services, and debugging deployments.
  • You are a polyglot and can work across languages (e.g. Elixir, Javascript, Python) with ease, knowing the ins and outs of each language (e.g. floating point math in Javascript), and are pragmatic about your language preferences.
  • You enjoy writing simple, elegant and idiomatic code.
  • You’re someone who can alternate between picking the best tool/language/framework for the job and making the best use of the tool right in front of you.
  • The idea of shipping code without a robust test suite gives you night sweats.
  • You’ve likely built dozens of edge cached, well documented REST APIs and have some exposure to GraphQL.
  • You’ve had the chance to design data platforms from the ground up and have seen your concepts validated (or debunked) at scale.

Computer Vision

  • You have 2-5 years ML related work experience with at least 1 year specialization in computer vision.
  • Advanced degree in mathematics/statistics is a plus but not required. Either way, you have a strong academic understanding of the science behind modern machine learning (e.g. linear algebra, statistics, optimization, algorithms).
  • You have practical experience implementing computer vision solutions, collaborating with a team, and shipping ML products at scale. 
  • You’ve worked with supervised, unsupervised, deep, and/or reinforcement learning algorithms. Specific applications of these algorithms include image segmentation, object detection/recognition, and classification.
  • You have experience in (and opinions about) OpenCV, modern deep learning frameworks (e.g. Pytorch, Tensorflow, Keras, MxNet, etc.), and on-device libraries like CoreML. 
  • Python is your (and our) native language, but you’ve been known to dabble in C++ on occasion. R enthusiasts are also welcome to apply! 
  • You feel compelled to explore the latest opportunities in the CV space, such as 3D scene reconstruction.
  • You find the idea of shipping robust models in the cloud and lean models on the edge to be an exciting challenge.
  • You are passionate about working with huge datasets and the data wrangling challenges they present, and are excited about ways to leverage this data in novel/interesting ways to users.
  • You have an opinion on machine learning debates (e.g. frequentist vs. bayesian view of the world, which deep learning library is the best, etc.) but also value pragmatism over dogmatic ideology.
  • You have excellent communication skills and can present a compelling argument for implementation of your solutions.
  • You have a rigorous attention to detail and quality of model input and output, and you obsess about validation metrics and train-test-validation datasets.


We want to get to know you! Send us an email at with your resume.


New York, Boston, Los Angeles, Detroit, Toronto, Shanghai

New York, Boston, Los Angeles, Detroit, Toronto, Shanghai


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