FlowCommand (YC W16) | Full-Stack Engineer, Data Engineer, Sensor Engineer | San Francisco | Onsite | $120k - $150k + 0.5% - 1.0% | https://angel.co/flowcommand
FlowCommand builds a new type of sensor and software system to monitor fluid infrastructure around the world for leaks, theft, spills, and performance. Fleets of our proprietary lightweight hardware generate raw acoustic data and then send that data directly to our server via cellular/satellite; we then use a mix of physics equations, signal processing, and anomaly detection to determine the behavior of fluid (volume and speed) in pipes.
A few upcoming projects:
We’re planning to send a robotic submarine 10,000 ft underwater to attach our sensors to pipelines sitting on the ocean floor, with the goal of detecting and stopping oil leaks that harm marine wildlife. Build the application that allows operators to monitor their pipeline for leaks and alert them to an impending environmental disaster.
Our Houston office has a remotely operable flow loop (ie an obstacle course for fluids) that allows us to approximate field conditions and gather raw acoustic data. The digital signal processing specialists who write our firmware need to capture test data, but the sensor processes millions of measurements per second, making it difficult to store and process the test data. Build a system that allows them to efficiently test their latest DSP algorithms under a variety of flow conditions.
Technologies we currently use
Web Apps: Python, Django, React
Data Pipeline: pandas, scikit-learn, Heroku/AWS
Sensor Firmware: C++, System Verilog
FlowCommand (YC W16) | Full-Stack Engineer, Data Engineer, Sensor Engineer | San Francisco | Onsite | $120k - $150k + 0.5% - 1.0% | https://angel.co/flowcommand
FlowCommand builds a new type of sensor and software system to monitor fluid infrastructure around the world for leaks, theft, spills, and performance. Fleets of our proprietary lightweight hardware generate raw acoustic data and then send that data directly to our server via cellular/satellite; we then use a mix of physics equations, signal processing, and anomaly detection to determine the behavior of fluid (volume and speed) in pipes.
A few upcoming projects:
We’re planning to send a robotic submarine 10,000 ft underwater to attach our sensors to pipelines sitting on the ocean floor, with the goal of detecting and stopping oil leaks that harm marine wildlife. Build the application that allows operators to monitor their pipeline for leaks and alert them to an impending environmental disaster.
Our Houston office has a remotely operable flow loop (ie an obstacle course for fluids) that allows us to approximate field conditions and gather raw acoustic data. The digital signal processing specialists who write our firmware need to capture test data, but the sensor processes millions of measurements per second, making it difficult to store and process the test data. Build a system that allows them to efficiently test their latest DSP algorithms under a variety of flow conditions.
Technologies we currently use:
Web Apps: Python, Django, React
Data Pipeline: pandas, scikit-learn, Heroku/AWS
Sensor Firmware: C++, System Verilog
Mayday is actually a killer feature on a phone for Grandma. With 24/7 on-device tech support, relatives would never have to field tech support requests.
FlowCommand builds a new type of sensor and software system to monitor fluid infrastructure around the world for leaks, theft, spills, and performance. Fleets of our proprietary lightweight hardware generate raw acoustic data and then send that data directly to our server via cellular/satellite; we then use a mix of physics equations, signal processing, and anomaly detection to determine the behavior of fluid (volume and speed) in pipes.
A few upcoming projects:
We’re planning to send a robotic submarine 10,000 ft underwater to attach our sensors to pipelines sitting on the ocean floor, with the goal of detecting and stopping oil leaks that harm marine wildlife. Build the application that allows operators to monitor their pipeline for leaks and alert them to an impending environmental disaster.
Our Houston office has a remotely operable flow loop (ie an obstacle course for fluids) that allows us to approximate field conditions and gather raw acoustic data. The digital signal processing specialists who write our firmware need to capture test data, but the sensor processes millions of measurements per second, making it difficult to store and process the test data. Build a system that allows them to efficiently test their latest DSP algorithms under a variety of flow conditions.
Technologies we currently use Web Apps: Python, Django, React Data Pipeline: pandas, scikit-learn, Heroku/AWS Sensor Firmware: C++, System Verilog
Please reach out at [email protected]