Machine Learning Engineer

Citizen; New York (NY); Remote; USD 220,000; Full time

Job summary

A leading public safety application provider is seeking an experienced Machine Learning Engineer to develop impactful features. You'll work on real-time audio transcription, improving data processing from IoT devices. The ideal candidate has over 5 years in ML and a strong foundation in related technologies. This position offers a competitive salary of $220,000 along with equity and comprehensive benefits in a hybrid work environment.

Benefits

100% employer-paid medical, dental, and vision

Unlimited PTO

Up to 14 weeks paid parental leave

Monthly tech stipend

Free mental health support

Catered lunches (NYC HQ)

Qualifications

• 5+ years experience leading and delivering effective ML solutions.
• Strong theoretical grounding in core Machine Learning concepts.
• Experience with ML for audio or natural language data is a bonus.

Responsibilities

• Drive the development of machine learning features to impact users.
• Work closely with operations to tune ML models and process data.
• Guide prioritization and impact analysis across ML initiatives.

Skills

Machine Learning techniques

Data analysis

Python

Data discretization

Deep neural networks

Education

Computer Science degree or related field

Tools

Kubernetes

Cassandra

MySQL

Google PubSub

Job description

Location

Remote

Employment Type

Full time

Location Type

Remote

Department

PEDDEngineering

About Citizen

Citizen is the #1 public safety app in the US, used by over 10 million people across 60+ U.S. cities to stay safe and informed in real time. Every piece of information is sourced directly from verified 911 data or live user reports. People have used Citizen to evacuate from fires, recover missing children, and avoid dangerous situations.

We offer three core products:

• Citizen (free): Real-time alerts, live incident maps, and community broadcasts

• Plus ($6/mo): Adds police scanners, crime stats, and customizable alert zones

• Premium ($20/mo): Connects users 24/7 to a trained safety agent who can track them, contact emergency services, and alert loved ones

• Our mission is simple: Protect the World. We're building the first global safety network where people protect each other — instantly and transparently. We've raised $100M+ from Founders Fund, 8VC, Goodwater, and Greycroft, and we're hiring builders who want to work on problems that matter.

About the Role

We are seeking an experienced Machine Learning Engineer to drive the development of critical, 0-to-1 features that bring real-world impact to our users. You will work closely with our operations team to tune and build ML models that process large volumes of radio information – transforming unstructured data into structured, actionable content for our users.

Citizen's information comes from a distributed network of IoT radio devices and as a ML expert you will be responsible for spearheading projects such as:

• Real-time audio transcription of highly variable radio data

• Association of non-serial information across time

• Detecting relevance and filtering noise from critical, potentially life-saving information

• Automatically generating structured content from unstructured audio/text streams

You’ll also guide prioritization and impact analysis across ML initiatives, help identify opportunities to leverage emerging AI/ML tooling, and ensure that our models scale reliably as we grow. If you’re a proactive and innovative individual with a passion for impactful machine learning and a track record of delivering production-grade solutions, we invite you to join us and shape the future of Citizen.

Our Challenges

• 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 scaling to a nationwide launch both technically and operationally.

• Bursting: We designed our infrastructure to scale without notice in case of a spontaneous event where we need to inform our entire user base. On significant events, we see hundreds of thousands of 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 police, fire, and medical audio every day to identify incidents that impact our users’ safety. Building robust ML models for audio analysis, event matching, and structured content creation at scale is a key priority.

Our Stack - languages and technologies we use and teach

• Services: Go for transactional systems; Python for analytical and ML systems

• Datastores: Cassandra, MySQL, Redis, Google PubSub

• Infrastructure: Kubernetes on Google Cloud; heavy utilization of OpenAI (GPT and Whisper) products with a growing base of internal ML infrastructure

Preferred Qualifications

• Computer Science degree or Machine Learning-related degree; or equivalent work experience in the field

• Strong theoretical grounding in core Machine Learning concepts and techniques

• Experience with a variety of ML techniques and frameworks, e.g. data discretization, normalization, sampling, linear regression, decision trees, SVMs, deep neural networks, etc

• 5+ years experience leading and delivering effective ML solutions for production use cases

• Bonus: experience with ML for audio or natural language data, and integrating ML pipelines with human-in-the-loop systems

Salary Range

This role offers a base salary of $220,000 - $220,000 per year, plus equity.

Compensation & Benefits
We offer competitive salary, equity, and a full benefits package, including:

• 100% employer-paid medical, dental, and vision for employees

• Unlimited PTO

• Up to 14 weeks paid parental leave (for all parents)

• Monthly tech stipend

• Free mental health support

• Hybrid work environment + catered lunches (NYC HQ)

Diversity, Equity & Inclusion at Citizen
Citizen is an equal opportunity employer. We’re building a team that reflects the diversity of the communities we serve — across race, gender identity, sexual orientation, age, ability, and background.

We know that diverse teams make better decisions and build more effective products. If you don’t meet every listed qualification, we still encourage you to apply. Skills, potential, and lived experience matter.