We're building the connected industrial workforce
Sr. Data Engineer$130k – $150k • 0.1% – 0.25%
Kinetic is an award-winning startup building connected wearable products for the industrial workforce. Our experienced team is backed by top tier VCs and insurance companies who share our passion for better predicting and reducing workplace injuries. Our technology is making sure the workers that physically support our economy, get home injury free.
Your role will be to allow the data science team to take their work to the next level. You will help them ingest large datasets, annotate video and sensor signals, and apply cutting edge machine learning techniques to our unique datasets. This role requires a strong software engineering background and a desire to work on exciting problems and unique environments. You should be passionate about tooling and developer experience, and motivated by new challenges.
You will have the opportunity to work with a wide variety of technologies in this role. You will also get to work on many green field projects, designing systems to solve complex problems most engineers never get to work on.
An ideal candidate will be familiar with Python, Go, or Scala. However this role is language agnostic. You will be able to (and even required) to build tools and systems with a wide variety of technologies and frameworks ranging for software that runs in embedded environments to systems run on big data map-reduce infrastructure. You are not required to be familiar with every technology you may use, but you should be a quick learner who is alway excited about new challenges.
You should be familiar with AWS and cloud architecture more broadly. You will work with Docker and similar tools on a daily basis. Experience with typical developer workflows (git, code reviews, and testing) are a must.
-You’ll work closely with the data science and the software engineering teams to build state of the art tooling and systems.
Build tools and systems to support collection of data, annotation of data, and training of models.
Build systems that can ingest millions to billions of data points and allow the data science team to access them as needed.
Build systems and process on top of cloud offerings including AWS and GCP to leverage data science tools are raw compute resources, while maintaining performance and security.
Build systems to make delivery of useful data to the data analytics team easy
Help solve tough machine-learning challenges including embedding complex models to run in real-time on extremely limited non-network attached hardware.
Help us deploy tools to quantify how much value we are adding to our clients by leveraging our large warehouse of sensor data.
5+ years professional software engineering experience
Passionate about tooling and developer productivity
Deeply knowledgeable with a variety of programming languages and systems.
Passionate about workflow and making sure the code is rigorously tested and reviewed
Comfortable working on small teams and taking ownership over codebases
You are familiar with technologies such as:
- AWS (especially Lambda, Kinesis, Redshift, S3, Athena etc.)
- SQL databases (Especially Postgres)
Bonus points for experience with:
- Hadoop and map-reduce frameworks (Flink, Storm, etc.)
- Mechanical Turk
If interested, please send your resume and some sentences about yourself to firstname.lastname@example.org.