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TITLE

 

Distributed Systems Engineer

COMPANY

 

Mist

LOCATION

 

Cupertino, CA, US

Description

About Mist

 

Mist built the first AI-driven wireless platform, designed specifically for the Smart Device Era. The Mist Learning Wireless LAN makes Wi-Fi predictable, reliable and measurable by providing unprecedented visibility into the user experience and by replacing time consuming manual IT tasks with proactive automation. In addition, Mist is the first vendor to bring enterprise-grade Wi-Fi, BLE and IoT together to deliver personalized, location-based wireless services without requiring battery-powered beacons. All operations are managed via Mist’s modern cloud architecture for maximum scalability, agility and performance.

 

The Mist team consists of leading experts in wireless, machine learning and cloud, who are responsible for building the largest and most advanced networks in the world. Founded in 2014, the company is based in Cupertino, CA and funded by top investors, including Lightspeed Venture Partners, Norwest Venture Partners, GV (formerly Google Ventures) and Cisco Investments. For more information, visit www.mist.com  

 

Distributed Systems (Distsys) Engineers at Mist are responsible for enabling the company do machine learning and anomaly detection in a distributed, scalable and cost effective way. No other WiFi company processes and analyzes data at a holistic level inside a single cloud which exposes significant opportunities for machine learning. Distsys engineers are specifically responsible for building, monitoring and maintaining the entire infrastructure which spans over a variety of open source and in-house distributed systems. We use open source systems like Kafka, Zookeeper, Cassandra, Storm, Mesos, along with a handful of Amazon Web Services (AWS). We have also built innovative in-house distributed stream processing solutions for aggregating thousands of metrics we generate every second.

 

 

 

Responsibilies:

 

Real-time streaming infrastructure: We are currently building our storm-based streaming infrastructure to enable our feature team to develop, deploy and quickly scale state of the art machine learned solutions.

Reliable message passing: Mist relies heavily on receiving and processing data from Wifi and BLE access points. We are currently using Kafka for message passing and reliability of our data. We are currently devising intelligent ways of auto-balancing kafka topics across our kafka cluster to operate smoothly.

Cluster management: We use Mesos to host all of our micro services. Hence, its important for us to ensure that our Mesos cluster is reliable and cost effective. We have formulated an innovative in-house solution that allows us to use EC2 spot instances for significant cost reductions over on-demand instances while improving cluster reliability.

Data management: Processing and storing data in an organized manner is an integral part of our core business. We use Postgres and cassandra to efficiently store and query data based on various use cases.

 

Requirements:

 

1+ year of industry experience

Strong understanding of:

distributed systems in general

multiprocessing and multithreading

Design and operation of massively scalable distributed systems

Strong programming skills and knowledge of data structures

Basic understanding of relational and NoSQL data stores

High level understanding of any open source distributed system like Kafka, Cassandra, Zookeeper, Hadoop, Storm, Spark or Mesos

 

 

Desirable:

 

Familiarity with Amazon Web Services (AWS)

In-depth knowledge of Unix and Linux

Masters/PhD in CS or related field

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