Cylera is a VC-backed stealth startup creating a network-level cybersecurity solution to manage and protect connected medical devices, such as infusion pumps and CT machines, by applying machine learning techniques to network traffic. Our problem space is at the intersection of the virtual and physical, where insecure medical equipment serves as the interface between patients and the hospital network, and where a single device compromise could have potentially life-threatening consequences.
Cloud Backend Engineer New York, NY, United States
Cybersecurity Researcher New York, NY, United States
Front-end UI/UX Engineer New York, NY, United States
Full-Stack Software Engineer New York, NY, United States
Low-Level Engineer New York, NY, United States
We have secured pilot partnerships with four large hospitals in the US, despite being a young pre-product company. These institutions have agreed to be early product champions who will help our team develop our platform to precisely meet the needs of the healthcare industry.
Our product is incredibly broad in technical scope (including low-level network packet processing and protocol decoding, a large-scale data processing pipeline running on Kubernetes, a machine/deep learning pipeline for cyber threat detection, and a full-stack web application for reporting and advanced visualizations, etc.) All engineering roles at Cylera will provide massive learning experiences, wrapped up in one of the fastest-growing technology sectors.
Our team has funding for at least two years of runway (even assuming no revenue!) from investors like Samsung NEXT. We are well on track to hit our metrics and outperform our expectations.
Our engineering team uses two-week sprint cycles. The cycle begins with a planning step where we discuss tasks, potential implementations, time estimates, and task assignment. The cycle ends with a sprint retrospective where we discuss how the sprint went and what could have been done to make it smoother. We encourage all members on the team to discuss, think about, and contribute to all parts of the product, even if it’s just providing high-level feedback on an idea. Our team uses Jira/Confluence/Github, with Jenkins for CI/CD. While different parts of the product have different testing frameworks, we strive to make the testing and deployment processes as automated and low-overhead as possible.
Working through interesting problems across a broad spectrum of domains is our normal day-to-day. While we are hiring multiple roles to focus on specific areas, we love engineers who are interesting in a variety of problems, even if it is a fresh learning experience for them.
Some challenges our team is tackling include:
- Designing algorithms to detect a medical/IoT device's identity purely based on its network-level behaviors
- Ingesting and storing large volumes of critical messages regarding medical device behaviors and abnormalities in a fault-tolerant, scalable way.
- Creating intelligent algorithms to detect stealthy, zero-day cyber attacks against medical devices on the wire
- Reverse engineering proprietary medical device protocols and creating a high-speed parser to extract relevant information in future traffic
- Tweaking high-end servers to deal with 10Gbps+ of network traffic per second with zero drops, including optimizations to the NIC drivers, kernel, and our application architecture
Turn a monolithic procedure into a scalable stream processing pipeline for converting raw network-level data into features for ingestion by our ML algorithms.
Decode a medical device's binary protocol, given network captures, and create a high-speed parser to extract fields of interest and pass them off to our feature ingestion engine.
Create an advanced medical device network topology visualization tool using D3 (or libraries on top of D3.)
Analyze data pertaining to known false positives/negatives outputted by our algorithm to brainstorm and implement algorithmic improvements to our threat detection algorithms.
Analyze network traffic from unknown IoT devices to determine their type and identify features that would be useful in the device's future detection.
Create integration layers with a variety of third-party tools such as Splunk, medical asset management systems, and firewalls.
Our small team has spent the past year hyper-focused on setting all the dominos in place: securing funding, building the right team, finding enthusiastic customers, and creating a solid technical foundation. While we recognize the massive market opportunity ahead of us, we are more excited by the problem space and the technological progress to be made. The idea that our code will protect life-critical medical devices from cyber attacks keeps us driven, focused, and brings us to work every day. We even have a bottle of champagne set aside for the day we stop our first attack.
Yet, while passion and grit have helped our scrappy team of five reach this point, we believe these traits were just the base requirements. Our individual drives to constantly learn, immerse ourselves in unfamiliar problem spaces and technologies, and balance desires for perfection with forward momentum have been critical. These are individual values we want to ensure we maintain as our small team rapidly grows over the next few months.
If any of this resonates with you at all, let's talk. We'd love for you to be there with us as we pop open that bottle of champagne.
Interested in this company?
Skip straight to final-round interviews by applying through Triplebyte.