Citizen is the No. 1 public safety app in the U.S., with a mission to make the world a safer place. Citizen provides 911 alerts so people can use their phones to keep themselves, and the people and places they love, safe. Citizen has notified people to evacuate burning buildings, deterred school buses from nearby terrorist attacks, and led to the rescue of kidnapped children and missing people.
Citizen’s 911 alerts are accompanied by live stories, real-time updates, and user-generated content so app users never have to wonder why there are helicopters overhead or fire engines passing by. By broadcasting from the scene of an incident, communicating with one another, and reading live updates, communities are empowered by Citizen. We act fast, break news, and give people the immediate information they need to stay safe. And we’re just getting started.
Our paid products—Citizen Protect and Citizen Plus, enhance the Citizen experience by offering users powerful features like police scanner radio, historical incidents, custom alerts zones, and access to a digital guardian 24/7 help. Subscribers have used Citizen Protect to de-escalate tense domestic situations, guide emergency response to remote hiking locations, travel safely on late-night walks and Ubers.
Already relied on by millions of people every day, Citizen will expand even further across the United States this year to keep more users safe and informed. We’re looking for hardworking, mission-driven individuals to help bring Citizen to hundreds of cities nationwide.
Citizen is backed by 8VC, Founders Fund, Goodwater Capital, and Greycroft and has raised $100M+ in VC funding.
About the Role:
We are seeking an experienced Machine Learning Engineer to lead initiatives and drive the development of key, net-new features. As the lead ML expert, you will be responsible for spearheading projects such as real-time audio transcription, relevance detection, and the conversion of unstructured information into structured content. Additionally, you will play a crucial role in improving the targeting capabilities of our notification system and enhancing our video operations through the development of models for moderating video content and optimizing thumbnail generation and selection. Your expertise will guide prioritization and impact analysis across ML initiatives, while also identifying opportunities to leverage new AI/ML tooling within our workflow. Furthermore, you will play a pivotal role in enhancing the rigor and accuracy of our predictive analytics, enabling us to predict users who are heading towards significant events, such as converting to paid plans or churning. If you are a proactive and innovative individual with a passion for machine learning and a track record of delivering impactful solutions, we invite you to join our team and help shape the future of our organization.
- Scaling: We have one of the fastest-growing organic user bases in key metropolitan areas, and have expanded to multiple other cities. We are focused on the nationwide launch and the need to support that scale.
- Bursting: We designed our infrastructure to scale without notice in case of a spontaneous incident where we need to inform our entire user base. On significant events, we see over a million simultaneously connected clients and their associated live streams. The core systems need to be able to efficiently support these traffic patterns and continue to scale to millions of more users in the future.
- Machine learning: We process thousands of hours of audio every day looking for incidents that impact our users’ safety. To do this at scale, we plan to build ML models for audio analysis and targeting using the current state of the art from academia.
- Analytics: We want to alert users to the incidents that matter to them, in a way that scales across different geographic densities and demographics.
- Mobile video streaming: Our app will ingest high-quality video at low-latency, transcode, and redistribute the video to external media outlets seamlessly.
- Radio hardware: We build our own software-defined radio-based devices to consume all radio dispatch in every major city, whether analog or digital.
Our Stack - languages and technologies we use and teach
- Mobile: Swift (iOS), Kotlin (Android)
- Web: React.js, TypeScript
- Services: Go for transactional systems; Python for analytical systems
- Datastores: Cassandra, MySQL, Redis, Google PubSub
- Infrastructure: Kubernetes on Google Cloud
- Computer Science degree or Machine Learning related degree; or equivalent work experience in the field
- Good theoretical grounding in core Machine Learning concepts and techniques
- Ability to reason about and grasp the intuition behind fundamental principles of Linear Algebra, Statistics, Probability
- Experience with a number of ML techniques and frameworks, e.g. data discretization, normalization, sampling, linear regression, decision trees, SVMs, deep neural networks, etc
- Familiarity with one or more DL software frameworks such as TensorFlow, PyTorch
- 3+ years experience leading and delivering effective ML solutions for large scale production use cases
Salary Range & Benefits:
The below represents the expected salary range for this position in New York, New York. We take a number of factors into account when determining compensation including your location, experience, and other job-related factors.
Salary Range: $190,000-$210,000 annually + equity + benefits
Citizen offers a competitive benefits package including medical, dental, vision, flexible spending accounts, paid time off, company holidays, stock option plan, commuter benefits, and various wellness perks.
Citizen is proud to be an equal opportunity employer. We provide employment opportunities without regard to age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, veteran status, or any other protected class.